NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
•Download as PPTX, PDF•
0 likes•246 views
This document summarizes the NCBO Resource Index, which is an ontology-based search tool that indexes over 16 billion annotations from over 200 ontologies and 3.5 million elements. It integrates information from diverse biomedical data sources and ontologies to improve search results through synonyms, hierarchies and mappings. The Resource Index is developed by the National Center for Biomedical Ontology to help users search for, find and explore biomedical resources.
Report
Share
Report
Share
Recommended
Data Mining 
Data mining techniques can help with biological data analysis in several ways:
1) They allow for the semantic integration of heterogeneous genomic and proteomic databases from different labs to enable cross-site analysis.
2) They facilitate alignment, indexing, similarity searching, and comparative analysis of multiple nucleotide and protein sequences, including building phylogenetic trees.
3) They enable the discovery of structural patterns and analysis of genetic networks and protein pathways, including prediction of protein structures and identification of regularities.
4) They support association and path analysis to identify co-occurring gene sequences and link genes to different stages of disease development, helping to develop more timely pharmaceutical interventions.
5) They provide visualization tools to aid in genetic data pattern
Pub med
PubMed is a free database of over 23 million citations and abstracts for biomedical literature from Medline, life sciences journals, and online books. It is maintained by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM). PubMed provides bibliographic information and links to full-text content from publishers and libraries. Users can search PubMed using keywords, controlled vocabularies like MeSH, or advanced search techniques and filters to find relevant journal articles and resources.
Chapter - 8.4 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
This document discusses mining sequence patterns in biological data. It begins with an overview of DNA structure and the central dogma of biology by which DNA is transcribed into RNA and translated into protein. It then describes several lab tools that can be used to determine biological data, such as DNA sequencers, mass spectrometry, and microarrays. The document concludes by noting that biological data mining can provide insights into biological processes and gain knowledge from abundant biological data sources.
Data mining ppt
This document discusses applications and trends in data mining for biological data analysis. It outlines how the explosive growth of genomics, proteomics, and biomedical research has led to the need for data mining techniques. Some key applications of data mining discussed include semantic integration of heterogeneous biological databases, sequence alignment and analysis, discovery of genetic networks and protein pathways, association analysis to identify co-occurring genes, and visualization tools. Biological data mining has become essential for research in bioinformatics.
Keeping up to date with information retrieval research: Summarized Research i...
The SuRe Info project aims to keep health technology assessment (HTA) information specialists up to date with information retrieval research. It has a team of international experts who collaborate online. The methodology involves identifying relevant studies, appraising them, and publishing chapters summarizing the research. To date, the project has appraised 34 studies and published 7 chapters, with 4 more in preparation. The goal is for SuRe Info to serve as an evidence-based resource for HTA information specialists and a platform for international collaboration.
Islt doctoral day may2018_marwa
This document discusses the toolbox of a PhD researcher and the PhD research life cycle. It provides information on several tools and resources for conducting research, including databases for searching information like Google Scholar and Sci-Hub, data analysis tools like Praat, PsychoPy, SPSS and R, and writing tools like Purdue OWL and Zotero. It also mentions different phases a PhD researcher goes through like a dreamer, lost, problem-solver and achiever. Overall, the document outlines key resources and steps to help PhD candidates in their research journey.
Ontology based phenotype database and mining tool
The Rat Genome Database has developed an ontology-based database and data mining tool to integrate rat phenotype data. The database uses four main ontologies - strain, clinical measurement, measurement method, and experimental conditions - to annotate phenotype data from various projects. This allows users to search and filter phenotype data based on these categories to compare results across studies and assist in choosing appropriate rat strains for their research. The tool also links phenotype data to genomic and genetic information to further understanding of variations.
Enabling Semantically Aware Software Applications
The National Center for Biomedical Ontology (NCBO) provides several software tools to enable semantically aware applications. These include BioPortal, an online library of biomedical ontologies, Ontology Widgets which allow integration of ontologies into websites, and the Annotator, a web service that semantically tags text with ontology terms. The NCBO also plans to develop a comprehensive index of online biomedical resources.
Recommended
Data Mining
Data mining techniques can help with biological data analysis in several ways:
1) They allow for the semantic integration of heterogeneous genomic and proteomic databases from different labs to enable cross-site analysis.
2) They facilitate alignment, indexing, similarity searching, and comparative analysis of multiple nucleotide and protein sequences, including building phylogenetic trees.
3) They enable the discovery of structural patterns and analysis of genetic networks and protein pathways, including prediction of protein structures and identification of regularities.
4) They support association and path analysis to identify co-occurring gene sequences and link genes to different stages of disease development, helping to develop more timely pharmaceutical interventions.
5) They provide visualization tools to aid in genetic data pattern
Pub med
PubMed is a free database of over 23 million citations and abstracts for biomedical literature from Medline, life sciences journals, and online books. It is maintained by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM). PubMed provides bibliographic information and links to full-text content from publishers and libraries. Users can search PubMed using keywords, controlled vocabularies like MeSH, or advanced search techniques and filters to find relevant journal articles and resources.
Chapter - 8.4 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
This document discusses mining sequence patterns in biological data. It begins with an overview of DNA structure and the central dogma of biology by which DNA is transcribed into RNA and translated into protein. It then describes several lab tools that can be used to determine biological data, such as DNA sequencers, mass spectrometry, and microarrays. The document concludes by noting that biological data mining can provide insights into biological processes and gain knowledge from abundant biological data sources.
Data mining ppt
This document discusses applications and trends in data mining for biological data analysis. It outlines how the explosive growth of genomics, proteomics, and biomedical research has led to the need for data mining techniques. Some key applications of data mining discussed include semantic integration of heterogeneous biological databases, sequence alignment and analysis, discovery of genetic networks and protein pathways, association analysis to identify co-occurring genes, and visualization tools. Biological data mining has become essential for research in bioinformatics.
Keeping up to date with information retrieval research: Summarized Research i...
The SuRe Info project aims to keep health technology assessment (HTA) information specialists up to date with information retrieval research. It has a team of international experts who collaborate online. The methodology involves identifying relevant studies, appraising them, and publishing chapters summarizing the research. To date, the project has appraised 34 studies and published 7 chapters, with 4 more in preparation. The goal is for SuRe Info to serve as an evidence-based resource for HTA information specialists and a platform for international collaboration.
Islt doctoral day may2018_marwa
This document discusses the toolbox of a PhD researcher and the PhD research life cycle. It provides information on several tools and resources for conducting research, including databases for searching information like Google Scholar and Sci-Hub, data analysis tools like Praat, PsychoPy, SPSS and R, and writing tools like Purdue OWL and Zotero. It also mentions different phases a PhD researcher goes through like a dreamer, lost, problem-solver and achiever. Overall, the document outlines key resources and steps to help PhD candidates in their research journey.
Ontology based phenotype database and mining tool
The Rat Genome Database has developed an ontology-based database and data mining tool to integrate rat phenotype data. The database uses four main ontologies - strain, clinical measurement, measurement method, and experimental conditions - to annotate phenotype data from various projects. This allows users to search and filter phenotype data based on these categories to compare results across studies and assist in choosing appropriate rat strains for their research. The tool also links phenotype data to genomic and genetic information to further understanding of variations.
Enabling Semantically Aware Software Applications
The National Center for Biomedical Ontology (NCBO) provides several software tools to enable semantically aware applications. These include BioPortal, an online library of biomedical ontologies, Ontology Widgets which allow integration of ontologies into websites, and the Annotator, a web service that semantically tags text with ontology terms. The NCBO also plans to develop a comprehensive index of online biomedical resources.
Applications of bioinformatics
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data.
Text mining in biomedical domain with emphasis on document clustering
This document summarizes a research article about using text mining techniques such as document clustering in the biomedical domain. It discusses how text mining can extract unknown knowledge from unstructured biomedical documents by preprocessing texts, applying natural language processing, and clustering or classifying documents. The techniques facilitate mining vast amounts of knowledge from published research that would otherwise be difficult to conclude without automated analysis.
Introduction to PubMed for LIS students
PubMed is a database of biomedical citations and abstracts maintained by the US National Library of Medicine. It contains over 20 million citations dating back to the 1950s. PubMed indexes MEDLINE citations and includes citations supplied by publishers as well as those in process. MeSH, or Medical Subject Headings, is a controlled vocabulary used for indexing articles in PubMed. Searching PubMed involves identifying key concepts in a search question and searching each concept separately before combining results. MyNCBI allows users to customize PubMed displays, save searches and collections. Alternative interfaces to PubMed include Pubget, LigerCat, and GoPubMed.
Bioinformatics for beginners (exam point of view)
. The term bioinformatics is coined by…………………………….
Paulien Hogeweg
2. What is an entry in database?
The process of entering data into a computerised database or spreadsheet.
3. Define BLASTp
BLAST- Basic Local Alignment Search Tool
It is a homology and similarity search tool.
It is provided by NCBI.
It is used to compare a query DNA sequence with a database of sequences.
4. What is Ecogenes?
Ecogene is a database and website and it is developed to improve structural and functional annotation of E.coli K-12 MG 1655.
Syntactic-semantic analysis for information extraction in biomedicine
Syntactic-semantic analysis for information extraction in biomedicineINESC-ID (Spoken Language Systems Laboratory - L2F)
This document discusses using syntactic-semantic analysis for information extraction in biomedicine. It aims to extract biomolecular events like phosphorylation from text. It uses dictionaries of entities and verbs associated with event types, and NooJ grammars to identify events. Evaluation on a shared task dataset shows average recall of 36.76% and precision of 65.58% for six event types. While results are promising, it discusses limitations like manual pattern identification and challenges with more complex event constructions.Recent trends in bioinformatics
This document discusses recent trends in bioinformatics, including the analysis of cDNA microarray data, protein tertiary structure prediction using Ramachandran plots, and the Protein Data Bank (PDB) which contains experimentally determined protein structures. It also discusses protein structure prediction techniques like CASP and TMW which aim to predict protein structures theoretically based on sequence. Predictions start from an initial conformation and use internal coordinates and planar geometry to model the structure as a tree. Further proteomics research can study protein function once a structure is obtained.
Evolution Phylogenetic
This document provides an overview of molecular phylogenetic analysis. It discusses how phylogenetic analysis uses molecular techniques to infer evolutionary relationships among organisms or genes. It describes common computational methods for phylogenetic analysis, including assembling and aligning datasets, and building phylogenetic trees. It also summarizes some online tools for phylogenetic analysis and discusses applications of molecular phylogenetics in different biological disciplines.
Characteristics of biological databases
Characteristics of biological databasesThapar Institute of Engineering & Technology, Patiala, Punjab, India
Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures. Biological databases can be broadly classified into sequence, structure and functional databases.COMPUTATIONAL METHODS FOR FUNCTIONAL ANALYSIS OF GENE EXPRESSION
Sequencing projects arising from high throughput technologies including those of sequencing DNA microarrays allowed to simultaneously measure the expression levels of millions of genes of a biological sample as well as annotate and identify the role (function) of those genes. Consequently, to better manage and organize this significant amount of information,
bioinformatics approaches have been developed. These approaches provide a representation and a more 'relevant' integration of data in order to test and validate the hypothesis of researchers throughout the experimental cycle. In this context, this article describes and discusses some of techniques used for the functional analysis of gene expression data.
Sequencedatabases
The document provides information about various biological sequence databases and bioinformatics tools and resources. It discusses nucleotide sequence databases like GenBank, EMBL, and DDBJ. It also mentions genome-centered databases like NCBI Genomes and Ensembl Genome Browser. Additionally, it covers protein databases like UniProt and PDB. It describes bioinformatics resources at EBI and NCBI like Entrez. Finally, it summarizes tools for sequence retrieval, comparison, and analysis like BLAST, sequence alignment, and genome browsers.
The researcher perspective, Jean-Fred Fontaine, MDC Berlin
This document discusses text and data mining for biomedical research. It describes how literature and molecular data have grown exponentially and challenges of accessing full texts. It outlines applications of text mining including document retrieval, discovery of gene-disease associations, and surveillance of surgical infections. Challenges include accuracy, moving from abstracts to full texts, and file formats.
Biomedical text mining
This document discusses biomedical text mining techniques used to extract information from scientific papers. It covers named entity recognition to identify concepts like proteins, chemicals and diseases. It also discusses information extraction to formalize facts stated in text, such as interactions between biological components. Techniques include co-mentioning analysis and natural language processing and tools have been applied to large text corpora to aid discovery.
3.[18 22]hybrid association rule mining using ac tree
This document proposes a new hybrid algorithm called AC Tree (AprioriCOFI tree) for efficiently mining association rules from large datasets at multiple concept levels. The AC Tree algorithm combines aspects of the Apriori, FP-Tree, and COFI Tree algorithms. It first uses Apriori to identify frequent 1-itemsets, then constructs an FP Tree header table and builds smaller trees for each frequent item to mine patterns at different levels. Experimental results on a 20 Newsgroups dataset show that AC Tree outperforms Apriori, FP-Tree, and APFT algorithms by discovering more interesting patterns faster.
521 524
The document discusses the design and implementation of a virtual client honeypot to collect internet malware. A client honeypot is an active security system that simulates client-side software to detect attacks against clients. The proposed virtual client honeypot collects URLs from a database, launches them in a virtual machine, and monitors for malware downloads and changes to the file system and network activity. The honeypot was able to successfully collect malware samples and network packet captures from malicious websites exploiting client-side vulnerabilities.
Seminar mol biol_1_spring_2013
The document discusses how bioinformatics can be used to identify new cancer drug targets. It describes analyzing gene sequences to find homologs of known cancer genes. Microarray data can be mined to find genes that are differentially expressed in cancer versus normal tissues. Digital expression data from EST and SAGE tags provides another method to analyze gene expression levels in cancers. Integrating these diverse genomic and expression datasets through bioinformatics allows detection of cancer-causing mutations, gene amplifications and differentially expressed genes to identify potential new drug targets.
335 340
This article discusses opportunities and challenges for efficient parallel data processing in cloud computing environments. It introduces Nephele, a new data processing framework designed specifically for clouds. Nephele is the first framework to leverage dynamic resource allocation in clouds for task scheduling and execution. The article analyzes how existing frameworks assume static resource environments unlike clouds, and how Nephele addresses this by dynamically allocating different compute resources during job execution. It then provides initial performance results for Nephele and compares it to Hadoop for MapReduce-style jobs on cloud infrastructure.
www.ijerd.com
This document describes a study that developed an integrated biomedical ontology for extracting information from Medline abstracts about Alzheimer's disease. The ontology integrated the Gene Ontology and Medical Subject Headings by mapping gene names, GO terms, and MeSH keywords related to Alzheimer's. The integrated ontology was validated structurally, syntactically, and semantically. It was then used to discover significant associations between proteins, genes, and Alzheimer's disease extracted from Medline abstracts.
The real world of ontologies and phenotype representation: perspectives from...
The document discusses the Neuroscience Information Framework (NIF) and its role in facilitating discovery and use of neuroscience resources through a consistent semantic framework. NIF provides a portal for searching various types of neuroscience data and information organized by categories. It utilizes ontologies and advanced technologies to allow simultaneous searching of multiple sources. Challenges include the large number of databases and other resources, differing data types, and inconsistent naming of brain structures across sources.
Diversity and Depth: Implementing AI across many long tail domains
Presentation at the IJCAI 2018 Industry Day
Elsevier serves researchers, doctors, and nurses. They have come to expect the same AI based services that they use in everyday life in their work environment, e.g.: recommendations, answer driven search, and summarized information. However, providing these sorts of services over the plethora of low resource domains that characterize science and medicine is a challenging proposition. (For example, most of the shelf NLP components are trained on newspaper corpora and exhibit much worse performance on scientific text). Furthermore, the level of precision expected in these domains is quite high. In this talk, we overview our efforts to overcome this challenge through the application of four techniques: 1) unsupervised learning; 2) leveraging of highly skilled but low volume expert annotators; 2) designing annotation tasks for non-experts in expert domains; and 4) transfer learning. We conclude with a series of open issues for the AI community stemming from our experience.
The Neuroscience Information Framework:The present and future of neuroscience...
The Neuroscience Information Framework:The present and future of neuroscience...Neuroscience Information Framework
The document discusses the Neuroscience Information Framework (NIF), which provides a portal for finding and utilizing web-based neuroscience resources. NIF allows simultaneous searching of multiple data sources through a concept-based interface organized by categories. It indexes over 35 million records from 65+ databases. NIF aims to address the challenges of dispersed and inconsistent neuroscience data by providing a common framework and tools to integrate data from various sources. Ontologies are discussed as a way to represent neuroscience concepts and relationships in a machine-readable way to facilitate data integration and querying across multiple scales and domains.RDAP14: Maryann Martone, Keynote, The Neuroscience Information Framework
The Neuroscience Information Framework (NIF) is an initiative of the NIH Blueprint to maximize access to and utility of worldwide neuroscience research resources. NIF catalogs over 10,000 resources including databases, literature, and materials. It provides search capabilities across these resources and develops ontologies and semantic frameworks to integrate diverse data types and scales. NIF aims to make dispersed neuroscience information more findable, accessible, interoperable, and reusable to enable new insights.
Resource Identification Initiative_RDA_March2014
Poster presentation about the Resource Identification Initiative (http://www.force11.org/Resource_identification_initiative) at the Research Data Alliance meeting in Dublin, Ireland in March 2014 (https://rd-alliance.org/rda-third-plenary-meeting.html).
More Related Content
What's hot
Applications of bioinformatics
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data.
Text mining in biomedical domain with emphasis on document clustering
This document summarizes a research article about using text mining techniques such as document clustering in the biomedical domain. It discusses how text mining can extract unknown knowledge from unstructured biomedical documents by preprocessing texts, applying natural language processing, and clustering or classifying documents. The techniques facilitate mining vast amounts of knowledge from published research that would otherwise be difficult to conclude without automated analysis.
Introduction to PubMed for LIS students
PubMed is a database of biomedical citations and abstracts maintained by the US National Library of Medicine. It contains over 20 million citations dating back to the 1950s. PubMed indexes MEDLINE citations and includes citations supplied by publishers as well as those in process. MeSH, or Medical Subject Headings, is a controlled vocabulary used for indexing articles in PubMed. Searching PubMed involves identifying key concepts in a search question and searching each concept separately before combining results. MyNCBI allows users to customize PubMed displays, save searches and collections. Alternative interfaces to PubMed include Pubget, LigerCat, and GoPubMed.
Bioinformatics for beginners (exam point of view)
. The term bioinformatics is coined by…………………………….
Paulien Hogeweg
2. What is an entry in database?
The process of entering data into a computerised database or spreadsheet.
3. Define BLASTp
BLAST- Basic Local Alignment Search Tool
It is a homology and similarity search tool.
It is provided by NCBI.
It is used to compare a query DNA sequence with a database of sequences.
4. What is Ecogenes?
Ecogene is a database and website and it is developed to improve structural and functional annotation of E.coli K-12 MG 1655.
Syntactic-semantic analysis for information extraction in biomedicine
Syntactic-semantic analysis for information extraction in biomedicineINESC-ID (Spoken Language Systems Laboratory - L2F)
This document discusses using syntactic-semantic analysis for information extraction in biomedicine. It aims to extract biomolecular events like phosphorylation from text. It uses dictionaries of entities and verbs associated with event types, and NooJ grammars to identify events. Evaluation on a shared task dataset shows average recall of 36.76% and precision of 65.58% for six event types. While results are promising, it discusses limitations like manual pattern identification and challenges with more complex event constructions.Recent trends in bioinformatics
This document discusses recent trends in bioinformatics, including the analysis of cDNA microarray data, protein tertiary structure prediction using Ramachandran plots, and the Protein Data Bank (PDB) which contains experimentally determined protein structures. It also discusses protein structure prediction techniques like CASP and TMW which aim to predict protein structures theoretically based on sequence. Predictions start from an initial conformation and use internal coordinates and planar geometry to model the structure as a tree. Further proteomics research can study protein function once a structure is obtained.
Evolution Phylogenetic
This document provides an overview of molecular phylogenetic analysis. It discusses how phylogenetic analysis uses molecular techniques to infer evolutionary relationships among organisms or genes. It describes common computational methods for phylogenetic analysis, including assembling and aligning datasets, and building phylogenetic trees. It also summarizes some online tools for phylogenetic analysis and discusses applications of molecular phylogenetics in different biological disciplines.
Characteristics of biological databases
Characteristics of biological databasesThapar Institute of Engineering & Technology, Patiala, Punjab, India
Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures. Biological databases can be broadly classified into sequence, structure and functional databases.COMPUTATIONAL METHODS FOR FUNCTIONAL ANALYSIS OF GENE EXPRESSION
Sequencing projects arising from high throughput technologies including those of sequencing DNA microarrays allowed to simultaneously measure the expression levels of millions of genes of a biological sample as well as annotate and identify the role (function) of those genes. Consequently, to better manage and organize this significant amount of information,
bioinformatics approaches have been developed. These approaches provide a representation and a more 'relevant' integration of data in order to test and validate the hypothesis of researchers throughout the experimental cycle. In this context, this article describes and discusses some of techniques used for the functional analysis of gene expression data.
Sequencedatabases
The document provides information about various biological sequence databases and bioinformatics tools and resources. It discusses nucleotide sequence databases like GenBank, EMBL, and DDBJ. It also mentions genome-centered databases like NCBI Genomes and Ensembl Genome Browser. Additionally, it covers protein databases like UniProt and PDB. It describes bioinformatics resources at EBI and NCBI like Entrez. Finally, it summarizes tools for sequence retrieval, comparison, and analysis like BLAST, sequence alignment, and genome browsers.
What's hot (10)
Text mining in biomedical domain with emphasis on document clustering
Text mining in biomedical domain with emphasis on document clustering
Syntactic-semantic analysis for information extraction in biomedicine
Syntactic-semantic analysis for information extraction in biomedicine
COMPUTATIONAL METHODS FOR FUNCTIONAL ANALYSIS OF GENE EXPRESSION
COMPUTATIONAL METHODS FOR FUNCTIONAL ANALYSIS OF GENE EXPRESSION
Viewers also liked
The researcher perspective, Jean-Fred Fontaine, MDC Berlin
This document discusses text and data mining for biomedical research. It describes how literature and molecular data have grown exponentially and challenges of accessing full texts. It outlines applications of text mining including document retrieval, discovery of gene-disease associations, and surveillance of surgical infections. Challenges include accuracy, moving from abstracts to full texts, and file formats.
Biomedical text mining
This document discusses biomedical text mining techniques used to extract information from scientific papers. It covers named entity recognition to identify concepts like proteins, chemicals and diseases. It also discusses information extraction to formalize facts stated in text, such as interactions between biological components. Techniques include co-mentioning analysis and natural language processing and tools have been applied to large text corpora to aid discovery.
3.[18 22]hybrid association rule mining using ac tree
This document proposes a new hybrid algorithm called AC Tree (AprioriCOFI tree) for efficiently mining association rules from large datasets at multiple concept levels. The AC Tree algorithm combines aspects of the Apriori, FP-Tree, and COFI Tree algorithms. It first uses Apriori to identify frequent 1-itemsets, then constructs an FP Tree header table and builds smaller trees for each frequent item to mine patterns at different levels. Experimental results on a 20 Newsgroups dataset show that AC Tree outperforms Apriori, FP-Tree, and APFT algorithms by discovering more interesting patterns faster.
521 524
The document discusses the design and implementation of a virtual client honeypot to collect internet malware. A client honeypot is an active security system that simulates client-side software to detect attacks against clients. The proposed virtual client honeypot collects URLs from a database, launches them in a virtual machine, and monitors for malware downloads and changes to the file system and network activity. The honeypot was able to successfully collect malware samples and network packet captures from malicious websites exploiting client-side vulnerabilities.
Seminar mol biol_1_spring_2013
The document discusses how bioinformatics can be used to identify new cancer drug targets. It describes analyzing gene sequences to find homologs of known cancer genes. Microarray data can be mined to find genes that are differentially expressed in cancer versus normal tissues. Digital expression data from EST and SAGE tags provides another method to analyze gene expression levels in cancers. Integrating these diverse genomic and expression datasets through bioinformatics allows detection of cancer-causing mutations, gene amplifications and differentially expressed genes to identify potential new drug targets.
335 340
This article discusses opportunities and challenges for efficient parallel data processing in cloud computing environments. It introduces Nephele, a new data processing framework designed specifically for clouds. Nephele is the first framework to leverage dynamic resource allocation in clouds for task scheduling and execution. The article analyzes how existing frameworks assume static resource environments unlike clouds, and how Nephele addresses this by dynamically allocating different compute resources during job execution. It then provides initial performance results for Nephele and compares it to Hadoop for MapReduce-style jobs on cloud infrastructure.
www.ijerd.com
This document describes a study that developed an integrated biomedical ontology for extracting information from Medline abstracts about Alzheimer's disease. The ontology integrated the Gene Ontology and Medical Subject Headings by mapping gene names, GO terms, and MeSH keywords related to Alzheimer's. The integrated ontology was validated structurally, syntactically, and semantically. It was then used to discover significant associations between proteins, genes, and Alzheimer's disease extracted from Medline abstracts.
Viewers also liked (7)
The researcher perspective, Jean-Fred Fontaine, MDC Berlin
The researcher perspective, Jean-Fred Fontaine, MDC Berlin
3.[18 22]hybrid association rule mining using ac tree
3.[18 22]hybrid association rule mining using ac tree
Similar to NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
The real world of ontologies and phenotype representation: perspectives from...
The document discusses the Neuroscience Information Framework (NIF) and its role in facilitating discovery and use of neuroscience resources through a consistent semantic framework. NIF provides a portal for searching various types of neuroscience data and information organized by categories. It utilizes ontologies and advanced technologies to allow simultaneous searching of multiple sources. Challenges include the large number of databases and other resources, differing data types, and inconsistent naming of brain structures across sources.
Diversity and Depth: Implementing AI across many long tail domains
Presentation at the IJCAI 2018 Industry Day
Elsevier serves researchers, doctors, and nurses. They have come to expect the same AI based services that they use in everyday life in their work environment, e.g.: recommendations, answer driven search, and summarized information. However, providing these sorts of services over the plethora of low resource domains that characterize science and medicine is a challenging proposition. (For example, most of the shelf NLP components are trained on newspaper corpora and exhibit much worse performance on scientific text). Furthermore, the level of precision expected in these domains is quite high. In this talk, we overview our efforts to overcome this challenge through the application of four techniques: 1) unsupervised learning; 2) leveraging of highly skilled but low volume expert annotators; 2) designing annotation tasks for non-experts in expert domains; and 4) transfer learning. We conclude with a series of open issues for the AI community stemming from our experience.
The Neuroscience Information Framework:The present and future of neuroscience...
The Neuroscience Information Framework:The present and future of neuroscience...Neuroscience Information Framework
The document discusses the Neuroscience Information Framework (NIF), which provides a portal for finding and utilizing web-based neuroscience resources. NIF allows simultaneous searching of multiple data sources through a concept-based interface organized by categories. It indexes over 35 million records from 65+ databases. NIF aims to address the challenges of dispersed and inconsistent neuroscience data by providing a common framework and tools to integrate data from various sources. Ontologies are discussed as a way to represent neuroscience concepts and relationships in a machine-readable way to facilitate data integration and querying across multiple scales and domains.RDAP14: Maryann Martone, Keynote, The Neuroscience Information Framework
The Neuroscience Information Framework (NIF) is an initiative of the NIH Blueprint to maximize access to and utility of worldwide neuroscience research resources. NIF catalogs over 10,000 resources including databases, literature, and materials. It provides search capabilities across these resources and develops ontologies and semantic frameworks to integrate diverse data types and scales. NIF aims to make dispersed neuroscience information more findable, accessible, interoperable, and reusable to enable new insights.
Resource Identification Initiative_RDA_March2014
Poster presentation about the Resource Identification Initiative (http://www.force11.org/Resource_identification_initiative) at the Research Data Alliance meeting in Dublin, Ireland in March 2014 (https://rd-alliance.org/rda-third-plenary-meeting.html).
Ti meadlt673litsearch
The literature search process involves several key steps: (1) identifying a specific research question using PICO elements - population, intervention, comparison, outcome; (2) searching the literature using keywords, controlled vocabulary, Boolean operators, and filters; (3) assessing the relevance of literature found; (4) synthesizing areas of agreement and disagreement between studies as well as new relevant findings; and (5) integrating findings into research proposals, papers or other work. The goal is to conduct a comprehensive review that places one's own research in the proper context.
Biomarkers brain regions
Learn how to use Pathway Studio to explore biomarkers and brain regions. With the addition of highly sophisticated visualization tools, users can interactively explore the vast number of connections created to help unravel disease biology. In addition, an innovative new taxonomy based on brain region identifications will be presented. Together, these innovations can be applied to rapidly increase the knowledge of diseases based on published findings.
Library Resources in Health Informatics
This document provides an overview of health informatics resources for a PATH 9100/4100F course. It discusses objectives to familiarize students with medical resources, databases, and search strategies. It also addresses clinical information needs within an evidence-based medicine framework. Key resources presented include PubMed, Scopus, UpToDate, DynaMed, and Cochrane Database. Search techniques like subject headings, citation tracking, and the pearl methodology framework are covered. Levels of evidence and filtered versus unfiltered information sources are also outlined. Contact information is provided for library assistance.
Effective search of bibliographic databases
This document provides guidance on effectively searching medical bibliographic databases. It begins by outlining the objectives of orienting the audience on how to search these databases and identifying appropriate databases. The introduction discusses the rapid growth of medical information and the importance of effectively reviewing previous literature. The document then describes several major medical bibliographic databases and how to access them. It provides a model for the information search process, including defining the research problem, choosing relevant databases, developing a search strategy, and evaluating results. Finally, it offers practical tips for searching, such as using Boolean operators and wildcards to account for variations in search terms.
research ppt1.pptx
The document discusses the importance of reviewing literature in the research process. It defines a literature review as an account of previous work and knowledge on a research topic. The main purposes of a literature review are to identify research problems, gaps in knowledge, and help guide methodology. Literature can be sourced from primary research as well as secondary sources like databases. Key databases discussed include CINAHL, MEDLINE, PubMed, and Cochrane. The document outlines criteria for selecting resources and a staged approach to conducting a literature review.
Pub Med
This document provides an overview of PubMed and how to search and use its bibliographic database. It discusses why PubMed is a powerful search tool, its database hierarchy, principles of information literacy, and strategies for retrieving and evaluating information found in PubMed searches. Key topics include using Medical Subject Headings (MeSH) terms and Boolean logic for effective searches, and features for saving, exporting, and managing search results.
Developing data services: a tale from two Oregon universities
While the generation or collection of large, complex research datasets is becoming easier and less expensive all the time, researchers often lack the knowledge and skills that are necessary to properly manage them. Having these skills is paramount in ensuring data quality, integrity, discoverability, integration, reproducibility, and reuse over time. Librarians have been preserving, managing and disseminating information for thousands of years. As scholarly research is increasingly carried out digitally, and products of research have expanded from primarily text-based manuscripts to include datasets, metadata, maps, software code etc., it is a natural expansion of scope for libraries to be involved in the stewardship of these materials as well. This kind of evolution requires that libraries bring in faculty with new skills and collaborate more intimately with researchers during the research data lifecycle, and this is exactly what is happening in academic libraries across the country. In this webinar, two researchers-turned-data-specialists, both based in academic libraries, will share their experiences and perspectives on the development of research data services at their respective institutions. Each will share their perspective on the important role that libraries can play in helping researchers manage, preserve, and share their data.
Connected Data for Machine Learning | Paul Groth
Elsevier aims to construct knowledge graphs to help address challenges in research and medicine. Knowledge graphs link entities like people, concepts, and events to provide answers. Elsevier analyzes text and data to build knowledge graphs using techniques like information extraction, machine learning, and predictive modeling. Their knowledge graph integrates data from publications, clinical records, and other sources to power applications that help researchers, medical professionals, and patients. Knowledge graphs are a critical component for delivering value, especially as data volumes and needs accelerate.
Introduction to health informatics : Research Questions
This document provides an overview of conducting a literature review in health informatics. It discusses formulating a research question, identifying relevant resources like PubMed and Scopus, developing search strategies using keywords and MeSH terms, evaluating search results, and organizing findings to write a literature review. PubMed is described as a biomedical database that can be searched using MeSH or keywords to locate journal citations and abstracts. Steps for structuring a PubMed search around a sample question on the efficiency of St. John's wort for smoking cessation are outlined.
How do we know what we don't know? Exploring the data and knowledge space th...
The document discusses the Neuroscience Information Framework (NIF), an initiative that aims to catalog and integrate neuroscience resources and data. NIF surveys the neuroscience resource landscape, currently cataloging over 3000 databases and datasets. It provides semantic integration of these resources through the use of ontologies and allows deep search of aggregated data. However, significant amounts of neuroscience data and resources remain inaccessible in publications, databases, and file drawers. Barriers to data sharing include lack of incentives, standards, and resources. NIF and related efforts aim to develop solutions to make more neuroscience data FAIR - findable, accessible, interoperable, and reusable.
Pub Med
This document provides an overview of the PubMed database. PubMed is an online database developed by the National Center for Biotechnology Information that allows users to access MEDLINE, a database of biomedical literature. The document discusses PubMed's history, coverage of over 19 million citations back to the 1950s, features like advanced search capabilities and links to full texts, and tutorials for searching and using PubMed.
Sharing data from clinical and medical research
Talk by Christoph Steinbeck, European Bioinformatics Institute (EMBL-EBI) on challenges for data sharing of clinical data in metabolomics research. This workshop was co-organised with the European BBMRI Biobanking infrastructure as part of the BioMedBridge symposium at the Wellcome Trust Conference Centre in Hinxton, UK.
Amia tb-review-12
This document provides a summary of the 2012 Translational Bioinformatics conference. It highlights several important papers presented at the conference in areas like systems medicine, finding and defining phenotypes, biomarkers, and genomic infrastructure. The document outlines the goals of the conference, the process used to select papers, caveats about the selection, and thanks various contributors. It then briefly summarizes several key papers from the conference in these areas.
Pub medpresentation
This document summarizes a presentation about the resource discovery tool PubMed. It notes that PubMed is developed by the National Library of Medicine, indexes over 21 million citations and abstracts in the biomedical and life sciences fields. The document outlines that PubMed's primary component is Medline, which indexes over 19 million journal article references over 60 years. Strengths of PubMed include that it is free, integrated with other NLM search engines, updated daily, and provides accurate search results. Weaknesses include a lack of citation analysis and sorting results by citations.
Pub medpresentation
This document summarizes a presentation about the resource discovery tool PubMed. It notes that PubMed is developed by the National Library of Medicine, indexes over 21 million citations and abstracts in the biomedical and life sciences fields. The document outlines that PubMed's primary component is Medline, which indexes over 19 million journal article references over 60 years. Strengths of PubMed include that it is free, integrated with other NLM search engines, updated daily, and provides accurate search results. Weaknesses include a lack of citation analysis and sorting results by citations.
Similar to NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources (20)
The real world of ontologies and phenotype representation: perspectives from...
The real world of ontologies and phenotype representation: perspectives from...
Diversity and Depth: Implementing AI across many long tail domains
Diversity and Depth: Implementing AI across many long tail domains
The Neuroscience Information Framework:The present and future of neuroscience...
The Neuroscience Information Framework:The present and future of neuroscience...
RDAP14: Maryann Martone, Keynote, The Neuroscience Information Framework
RDAP14: Maryann Martone, Keynote, The Neuroscience Information Framework
Developing data services: a tale from two Oregon universities
Developing data services: a tale from two Oregon universities
Introduction to health informatics : Research Questions
Introduction to health informatics : Research Questions
How do we know what we don't know? Exploring the data and knowledge space th...
How do we know what we don't know? Exploring the data and knowledge space th...
More from Trish Whetzel
Building Translate on Glass
Slides from the Women Hacking Glass session. The slides describe how to use the Google Translate API within a Glass app.
NCBO Web Services: Powering Semantically Aware Applications
The National Center for Biomedical Ontology provides web services and tools to enable the application of ontologies in biomedical science and clinical care. It maintains a library of biomedical ontologies and builds tools for ontology development, data annotation, and data integration. Key web services include services for ontology search, traversal, and download, as well as annotation and mapping services.
NCBO SPARQL Endpoint
The document describes the NCBO SPARQL endpoint, which provides access to ontologies from the BioPortal in RDF format. It can be queried using SPARQL. The endpoint contains over 393 ontologies with 4.2 million terms and 80 million triples. Examples are provided to retrieve ontology metadata and terms. Performance tips recommend using UNIONS instead of FILTERS for optimized queries.
NCBO Technology Overview
The document provides an overview of the National Center for Biomedical Ontology (NCBO) technology including REST web services, the BioPortal ontology repository, NCBO web services, and the BioPortal SPARQL endpoint. Key NCBO web services allow users to search ontologies, access ontology terms and hierarchies, propose term annotations, map between ontologies, and annotate data with ontology terms. The document outlines several NCBO tools and resources available for working with biomedical ontologies.
BioPortal: ontologies and integrated data resources
BioPortal is a website hosted by the National Center for Biomedical Ontology that allows users to browse, search, and utilize various biomedical ontologies and integrated data resources. It contains ontologies related to different domains in biomedicine as well as tools to facilitate the annotation and integration of data using the ontologies.
Web Services for Semantic Applications in Healthcare and Life Sciences
The document discusses web services for semantic applications in healthcare and life sciences. It describes RESTful web services that use HTTP and unique URLs to represent objects. It also discusses BioPortal, an ontology repository that allows browsing, searching, and visualizing ontologies in various formats. Tools are presented that use ontology web services and BioPortal for tasks like ontology term selection, automated recognition of terms before publication, and annotation within visualizations.
NCBO Technology for GSC15
The National Center for Biomedical Ontology (NCBO) provides access to biomedical ontologies through its BioPortal repository and suite of web services. BioPortal stores and allows viewing, browsing, and searching across ontologies. The NCBO web services enable programmatic access and enable functions like searching, traversing, and annotating terms. Several software applications leverage the NCBO web services by integrating access to ontologies to provide features like term tagging.
Ontology Web Services
The National Center for Biomedical Ontology provides several ontology web services including:
1) Accessing ontologies and ontology views through services like search, term access, and hierarchy visualization.
2) Creating ontology-based annotations on text data through services like annotation and ontology recommendation.
3) Indexing annotations in a resource index to facilitate search and discovery of annotated resources.
NCBO Tools and Web services
The document describes tools and web services from the National Center for Biomedical Ontology (NCBO) including the Ontology Web Services, Ontology Widgets, NCBO Annotator, NCBO Resource Index, and Ontology Recommender. The NCBO Annotator is an open access web service that annotates text with terms from ontologies in BioPortal and includes a variety of customization parameters. The NCBO Resource Index provides an ontology-based search across publicly available biomedical resources.
Ontology Web services for Semantic Applications
The document describes ontology web services created by the National Center for Biomedical Ontology to facilitate the application of ontologies in biomedical science. The services provide access to ontologies and related functions like searching, term details, hierarchies and mappings. Additional services allow the creation of ontology-based annotations using tools like the annotator and ontology recommender. All services are accessible via RESTful web APIs.
NCBO Technology
The National Center for Biomedical Ontology (NCBO) creates software and tools to enable the application of ontologies in biomedical science. It maintains a library of biomedical ontologies in BioPortal and provides web services and applications to access, integrate and annotate data with ontologies. Key activities include building tools like Protégé, BioPortal, the annotator and providing a SPARQL endpoint to access ontology data in RDF format.
CTSA Inventory Resource Web Presence
The document describes the CTSA Inventory Resource Web Presence (CIRWP), a web-accessible and searchable inventory of research resources across the CTSA consortium. It outlines the development of CIRWP, including building an informatics infrastructure based on standards, extending ontologies to annotate resource descriptions, and deploying web services and tools to enable a distributed inventory. CIRWP includes full or partial inventories from 37 CTSA sites cataloging over 370 informatics resources. The document discusses future goals of CIRWP such as accelerating harmonization across organizations and outreach, and highlights evaluations conducted to design CIRWP with user-centered approaches.
NCBO BioPortal SPARQL Endpoint - The Quad Economy of a Semantic Web Ontology ...
The document discusses the NCBO BioPortal SPARQL endpoint, which provides query access to ontologies stored in BioPortal. It analyzes storing ontologies in a quad store to improve scalability over materializing all import closures. An analysis of 149 OWL ontologies found materializing imports led to nearly double the number of ontologies and triples compared to using individual ontology graphs without import materialization. The SPARQL endpoint facilitates queries across ontologies by synchronizing content daily and providing access to ontology metadata and versions.
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
The document discusses the NCBO Annotator and its ability to annotate clinical notes with terms from over 250 biomedical ontologies. The annotator can process up to 1 million clinical notes per hour and adds features like negation detection. It was used to annotate notes from over 1.04 million patients to allow for pattern analysis and enrichment analysis related to drug safety and off-label drug use with the Human Disease Ontology.
Annotation Analysis for Testing Drug Safety Signals
The NCBO Annotator enables mining clinical documents by:
1) Tagging textual metadata from clinical documents with terms from biomedical ontologies.
2) Using the tagged data to perform further analysis like identifying adverse drug events and patterns of off-label drug use.
3) Future work includes expanding from individual term recognition to identifying expert-defined patterns involving terms for tasks like determining smoking status and medication dosages from notes.
Collaborative Development of Ontologies using BioPortal and WebProtégé
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. It also provides analytics. The integration allows editors to see comments in context and make changes, with comments archived once tasks are complete. This provides a full lifecycle of ontology development, feedback, and refinement.
NCBO Overview and Biositemaps
The document describes the National Center for Biomedical Ontology (NCBO) and Biositemaps. It discusses:
1) The NCBO's mission to create software for applying ontologies in biomedicine and its partners including Stanford University, Mayo Clinic, and University of Buffalo.
2) Biositemaps which provide a machine-readable description of biomedical resources using an information model based on the Biomedical Resource Ontology to enable discovery by search engines.
3) How Biositemaps has grown from an initial wiki listing resources by the National Centers for Biomedical Computing to a catalog of over 1,400 resources shared using a standardized framework.
Biomedical Resource Ontology
The document describes the Biomedical Resource Ontology (BRO), which provides semantics for annotating resources in Biositemaps. BRO defines types of resources, activities, and areas of research. It has been applied in tools for editing, searching, and discovering resources across multiple institutions. Ongoing work involves expanding BRO terms, separating the ontology from the information model, and integrating with other related projects.
NCBO Web services: Powering Semantically Aware Applications
The National Center for Biomedical Ontology provides several web services to enable semantically aware applications, including services for ontology development and visualization, data annotation, and data integration. These services include tools for ontology search, traversal, mapping, and comment as well as services for term recognition, annotation, and access to annotated data. Documentation for using these services is available on the NCBO website.
Collaborative Development of Ontologies using BioPortal and WebProtégé
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. This integrated platform allows ontology editors to see comments in context and update the ontology accordingly.
More from Trish Whetzel (20)
NCBO Web Services: Powering Semantically Aware Applications
NCBO Web Services: Powering Semantically Aware Applications
BioPortal: ontologies and integrated data resources
BioPortal: ontologies and integrated data resources
Web Services for Semantic Applications in Healthcare and Life Sciences
Web Services for Semantic Applications in Healthcare and Life Sciences
NCBO BioPortal SPARQL Endpoint - The Quad Economy of a Semantic Web Ontology ...
NCBO BioPortal SPARQL Endpoint - The Quad Economy of a Semantic Web Ontology ...
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
Annotation Analysis for Testing Drug Safety Signals
Annotation Analysis for Testing Drug Safety Signals
Collaborative Development of Ontologies using BioPortal and WebProtégé
Collaborative Development of Ontologies using BioPortal and WebProtégé
NCBO Web services: Powering Semantically Aware Applications
NCBO Web services: Powering Semantically Aware Applications
Collaborative Development of Ontologies using BioPortal and WebProtégé
Collaborative Development of Ontologies using BioPortal and WebProtégé
Recently uploaded
一比一原版(USF毕业证)旧金山大学毕业证如何办理
USF硕士毕业证成绩单【微信95270640】一比一伪造旧金山大学文凭@假冒USF毕业证成绩单+Q微信95270640办理USF学位证书@仿造USF毕业文凭证书@购买旧金山大学毕业证成绩单USF真实使馆认证/真实留信认证回国人员证明
#一整套旧金山大学文凭证件办理#—包含旧金山大学旧金山大学本科毕业证成绩单学历认证|使馆认证|归国人员证明|教育部认证|留信网认证永远存档教育部学历学位认证查询办理国外文凭国外学历学位认证#我们提供全套办理服务。
一整套留学文凭证件服务：
一：旧金山大学旧金山大学本科毕业证成绩单毕业证 #成绩单等全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站永久可查
四：留信认证留学生信息网站永久可查
国外毕业证学位证成绩单办理方法：
1客户提供办理旧金山大学旧金山大学本科毕业证成绩单信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
教育部文凭学历认证认证的用途：
如果您计划在国内发展那么办理国内教育部认证是必不可少的。事业性用人单位如银行国企公务员在您应聘时都会需要您提供这个认证。其他私营 #外企企业无需提供！办理教育部认证所需资料众多且烦琐所有材料您都必须提供原件我们凭借丰富的经验帮您快速整合材料让您少走弯路。
实体公司专业为您服务如有需要请联系我: 微信95270640奈一次次令他失望山娃今年岁上五年级识得很多字从走出小屋开始山娃就知道父亲的家和工地共有一个很动听的名字——天河工地的底层空空荡荡很宽阔很凉爽在地上铺上报纸和水泥袋父亲和工人们中午全睡在地上地面坑坑洼洼山娃曾多次绊倒过也曾有长铁钉穿透凉鞋刺在脚板上但山娃不怕工地上也常有五六个从乡下来的小学生他们的父母亲也是高楼上的建筑工人小伙伴来自不同省份都操着带有浓重口音的普通话可不知为啥山娃不仅很快与他们熟识了
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.ACE - Team 24 Wrapup event at ahmedabad.
Atlassian Team 24 event wrap-up Ahmedabad. Recap of Atlassian team24 event.
Upturn India Technologies - Web development company in Nashik
Nashik's top web development company, Upturn India Technologies, crafts innovative digital solutions for your success. Partner with us and achieve your goals
Orca: Nocode Graphical Editor for Container Orchestration
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
如何办理(hull学位证书)英国赫尔大学毕业证硕士文凭原版一模一样
原版定制【微信:bwp0011】《(hull学位证书)英国赫尔大学毕业证硕士文凭》【微信:bwp0011】成绩单 、雅思、外壳、留信学历认证永久存档查询，采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信bwp0011】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信bwp0011】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
How GenAI Can Improve Supplier Performance Management.pdf
Data Collection and Analysis with GenAI enables organizations to gather, analyze, and visualize vast amounts of supplier data, identifying key performance indicators and trends. Predictive analytics forecast future supplier performance, mitigating risks and seizing opportunities. Supplier segmentation allows for tailored management strategies, optimizing resource allocation. Automated scorecards and reporting provide real-time insights, enhancing transparency and tracking progress. Collaboration is fostered through GenAI-powered platforms, driving continuous improvement. NLP analyzes unstructured feedback, uncovering deeper insights into supplier relationships. Simulation and scenario planning tools anticipate supply chain disruptions, supporting informed decision-making. Integration with existing systems enhances data accuracy and consistency. McKinsey estimates GenAI could deliver $2.6 trillion to $4.4 trillion in economic benefits annually across industries, revolutionizing procurement processes and delivering significant ROI.
Safelyio Toolbox Talk Softwate & App (How To Digitize Safety Meetings)
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Voxxed Days Trieste 2024 - Unleashing the Power of Vector Search and Semantic...
Vector databases are redefining data handling, enabling semantic searches across text, images, and audio encoded as vectors.
Redis OM for Java simplifies this innovative approach, making it accessible even for those new to vector data.
This presentation explores the cutting-edge features of vector search and semantic caching in Java, highlighting the Redis OM library through a demonstration application.
Redis OM has evolved to embrace the transformative world of vector database technology, now supporting Redis vector search and seamless integration with OpenAI, Hugging Face, LangChain, and LlamaIndex. This talk highlights the latest advancements in Redis OM, focusing on how it simplifies the complex process of vector indexing, data modeling, and querying for AI-powered applications. We will explore the new capabilities of Redis OM, including intuitive vector search interfaces and semantic caching, which reduce the overhead of large language model (LLM) calls.
42 Ways to Generate Real Estate Leads - Sellxpert
Generate hot real estate leads with these simple strategies. 42 innovative ways to attract clients in the real estate industry.
Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
Assure Contact Center Experiences for Your Customers With ThousandEyes
Assure Contact Center Experiences for Your Customers With ThousandEyes
Penify - Let AI do the Documentation, you write the Code.
Penify automates the software documentation process for Git repositories. Every time a code modification is merged into "main", Penify uses a Large Language Model to generate documentation for the updated code. This automation covers multiple documentation layers, including InCode Documentation, API Documentation, Architectural Documentation, and PR documentation, each designed to improve different aspects of the development process. By taking over the entire documentation process, Penify tackles the common problem of documentation becoming outdated as the code evolves.
https://www.penify.dev/
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻
Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
WWDC 2024 Keynote Review: For CocoaCoders Austin
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
Modelling Up - DDDEurope 2024 - Amsterdam
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...
In today's fiercely competitive mobile app market, the role of the QA team is pivotal for continuous improvement and sustained success. Effective testing strategies are essential to navigate the challenges confidently and precisely. Ensuring the perfection of mobile apps before they reach end-users requires thoughtful decisions in the testing plan.
ppt on the brain chip neuralink.pptx
A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions.
Recently uploaded (20)
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...
Upturn India Technologies - Web development company in Nashik
Upturn India Technologies - Web development company in Nashik
Orca: Nocode Graphical Editor for Container Orchestration
Orca: Nocode Graphical Editor for Container Orchestration
How GenAI Can Improve Supplier Performance Management.pdf
How GenAI Can Improve Supplier Performance Management.pdf
Safelyio Toolbox Talk Softwate & App (How To Digitize Safety Meetings)
Safelyio Toolbox Talk Softwate & App (How To Digitize Safety Meetings)
Voxxed Days Trieste 2024 - Unleashing the Power of Vector Search and Semantic...
Voxxed Days Trieste 2024 - Unleashing the Power of Vector Search and Semantic...
Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
Assure Contact Center Experiences for Your Customers With ThousandEyes
Assure Contact Center Experiences for Your Customers With ThousandEyes
Penify - Let AI do the Documentation, you write the Code.
Penify - Let AI do the Documentation, you write the Code.
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...
NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
- 1. 22 sources NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources Patricia L. Whetzel1, Clement Jonquet2, Paea LePendu1, Sean M. Falconer1, Adrien Coulet3, 3.5M elements 2 200 ontologies Without: No items found. Why not? Because adrenal gland pheochromocytoma is a specialization of retroperitoneal neoplasm (for example), which we know by using ontologies, so we can find results where others may not. 2.4M terms 4M mappings 16.4 Billion Annotations Indexed End User Application: NCBO Resource Index Search • Search. Find. Explore. Ontologies help to integrate diverse resources, 1 to guide the user, and to improve search results. Diverse Information Sources • Resources. Elements. Ontologies. We combine knowledge from many different data sources and ontologies contributed and maintained by other researchers from all over the world. 3 Meaning • Synonyms. Hierarchies. Mappings. Under the hood, we expand and rank search results based on various semantic elements. retroperitoneal neoplasm Search Natalya F. Noy1, Mark A. Musen1, Nigam H. Shah1 1Stanford University, USA, 2Université Montpellier, France, 3Nancy University, France Acknowledgements The Resource Index is developed by the National Center for Biomedical Ontology (NCBO), one of the National Centers for Biomedical Computing under the NIH Roadmap. For more information on NCBO and working with the Center, visit http://www.bioontology.org or email support@bioontology.org. Auto-complete using terminologies Filter by related terms View details Features With: 20 search results! Try it! http://bioportal.bioontology.org/resources