BioGPS is a community-driven, customizable gene annotation portal that allows users to query genes and view gene reports. It aggregates information from over 400 gene databases and resources contributed by users. Users can customize the layout and content of gene reports. The portal has had over 680,000 gene queries, 800,000 gene reports viewed, and 400 resources added by users in the last year. An associated MyGene.Info service provides programmatic access to gene annotation data.
BioGPS is a community-driven, customizable gene annotation portal that aims to:
1) Provide easy access to numerous gene databases and resources through a single interface.
2) Allow users to customize their gene reports and views based on their specific interests and needs.
3) Encourage contributions from the broader research community to expand the number of available gene annotation resources and plugins.
MyGene.info is a gene web service that contains over 17 million genes from more than 14,000 species with over 50 different annotation types. It has two simple endpoints for querying gene hits and retrieving gene annotations without requiring signup or an API key. The service is blazing fast, up-to-date on a weekly basis, scalable to support thousands of concurrent users, and can easily scale up to meet increased demand.
The document describes MyGene.info, an elastic gene API that provides fast, always-on, up-to-date, and scalable access to gene data through public and private query instances. It retrieves data from sources like Entrez and Ensembl, merges them into a single gene object, and stores the objects in a NoSQL database. The public query instance syncs updated gene data from a public data hub and allows flexible queries over >40 fields for all species. Private instances also sync from the public hub but can merge in additional private data.
Metodologia e processo da alfabetizacão das séries iniciaiscefaprodematupa
Este documento discute a metodologia e o processo de alfabetização nas séries iniciais. Ele revela que as dificuldades na leitura e interpretação de textos ocorrem devido à falta de educação de qualidade e incentivo à leitura. Além disso, as condições sócioeconômicas das crianças também causam problemas. Uma boa metodologia deve levar em conta a realidade da criança e o que ela já sabe.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
1) The document discusses the opportunity for technology to improve organizational efficiency and transition economies into a "smart and clean world."
2) It argues that aggregate efficiency has stalled at around 22% for 30 years due to limitations of the Second Industrial Revolution, but that digitizing transport, energy, and communication through technologies like blockchain can help manage resources and increase efficiency.
3) Technologies like precision agriculture, cloud computing, robotics, and autonomous vehicles may allow for "dematerialization" and do more with fewer physical resources through effects like reduced waste and need for transportation/logistics infrastructure.
BITS: Overview of important biological databases beyond sequencesBITS
Module 4 Other relevant biological data sources beyond sequences
Part of training session "Basic Bioinformatics concepts, databases and tools" - http://www.bits.vib.be/training
BioGPS is a community-driven, customizable gene annotation portal that aims to:
1) Provide easy access to numerous gene databases and resources through a single interface.
2) Allow users to customize their gene reports and views based on their specific interests and needs.
3) Encourage contributions from the broader research community to expand the number of available gene annotation resources and plugins.
MyGene.info is a gene web service that contains over 17 million genes from more than 14,000 species with over 50 different annotation types. It has two simple endpoints for querying gene hits and retrieving gene annotations without requiring signup or an API key. The service is blazing fast, up-to-date on a weekly basis, scalable to support thousands of concurrent users, and can easily scale up to meet increased demand.
The document describes MyGene.info, an elastic gene API that provides fast, always-on, up-to-date, and scalable access to gene data through public and private query instances. It retrieves data from sources like Entrez and Ensembl, merges them into a single gene object, and stores the objects in a NoSQL database. The public query instance syncs updated gene data from a public data hub and allows flexible queries over >40 fields for all species. Private instances also sync from the public hub but can merge in additional private data.
Metodologia e processo da alfabetizacão das séries iniciaiscefaprodematupa
Este documento discute a metodologia e o processo de alfabetização nas séries iniciais. Ele revela que as dificuldades na leitura e interpretação de textos ocorrem devido à falta de educação de qualidade e incentivo à leitura. Além disso, as condições sócioeconômicas das crianças também causam problemas. Uma boa metodologia deve levar em conta a realidade da criança e o que ela já sabe.
Reuters: Pictures of the Year 2016 (Part 2)maditabalnco
This document contains 20 photos from news events around the world between January and November 2016. The photos show international events like the US presidential election, the conflict in Ukraine, the migrant crisis in Europe, the Rio Olympics, and more. They also depict human interest stories and natural phenomena from various countries.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
1) The document discusses the opportunity for technology to improve organizational efficiency and transition economies into a "smart and clean world."
2) It argues that aggregate efficiency has stalled at around 22% for 30 years due to limitations of the Second Industrial Revolution, but that digitizing transport, energy, and communication through technologies like blockchain can help manage resources and increase efficiency.
3) Technologies like precision agriculture, cloud computing, robotics, and autonomous vehicles may allow for "dematerialization" and do more with fewer physical resources through effects like reduced waste and need for transportation/logistics infrastructure.
BITS: Overview of important biological databases beyond sequencesBITS
Module 4 Other relevant biological data sources beyond sequences
Part of training session "Basic Bioinformatics concepts, databases and tools" - http://www.bits.vib.be/training
This document discusses the ISA Commons project, which aims to facilitate sharing of life science experiments using a common structured representation. It does this by [1] using a format that can describe experiments across domains, [2] following community standards and norms, and [3] being implemented in curation and data sharing tools. The presentation outlines challenges around inconsistent reporting and many related standards, and describes how ISA Commons addresses these through its metadata tracking framework and software suite. This enables standardized experimental annotation and data sharing across a growing number of public resources and research groups.
Role of bioinformatics in life sciences researchAnshika Bansal
1. The document discusses bioinformatics and summarizes some of its key applications and tools. It describes how bioinformatics merges biology and computer science to solve biological problems by applying computational tools to molecular data.
2. It provides examples of common bioinformatics tasks like retrieving sequences from databases, comparing sequences, analyzing genes and proteins, and viewing 3D structures.
3. The document lists several popular databases for nucleotide sequences, protein sequences, literature, and other biological data. It also introduces common bioinformatics tools for tasks like sequence alignment, translation, and structure analysis.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk about BioThings API project at ISMB 2018 Chicago, as part of BD2K special session. BioThings API project provides a collection of high-performance APIs (MyGene.info, MyVariant.info, MyChem.info), an SDK for building a new biomedical API (BioThings SDK), and a JSON-LD and OpenAPI based solution for across-API interoperability and knowledge exploration.
1. This document provides a detailed protocol for performing GO and KEGG enrichment analysis on gene lists from rice (Oryza sativa).
2. It describes obtaining GO and KEGG annotations from public databases and an R package, and using the clusterProfiler package in R for enrichment analysis and visualization of results.
3. GO enrichment analysis using self-curated annotation files from rice databases identified 29 enriched GO terms, while KEGG enrichment analysis identified 11 enriched pathways.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk at NCI's CBIIT speaker series:
https://wiki.nci.nih.gov/display/CBIITSpeakers/2019/01/02/Jan+16%2C+Chunlei+Wu%2C+BioThings+API
A companion blog post: https://ncip.nci.nih.gov/blog/the-network-of-biothings/
See more details about BioThings project at http://biothings.io.
Bioinformatic Harvester is a software tool that acts as a meta search engine for genes and protein information. It collects and indexes data from 16 major bioinformatics databases and allows users to search across these databases simultaneously. Search results are displayed on a single HTML page and are ranked based on relevance. Users can query the system using terms like gene names, sequences, protein domains, and literature to retrieve integrated information from databases on genes and proteins.
Using ontologies to do integrative systems biologyChris Evelo
The document discusses using ontologies to integrate systems biology data. It describes typical steps in systems biology studies such as finding studies, processing data, integrating data, and combining data from multiple sources. Ontologies can help link information from different analysis techniques and combine data from many studies by capturing study metadata. The document advocates using standards like ISA-TAB and MAGE-TAB to capture study data and proposes using a generic study capture framework with modular components to integrate different types of 'omics data. Ontologies are needed for collaboration and to provide controlled vocabularies for annotation.
The document discusses various types of biological databases. It describes primary databases that contain original data, secondary databases that contain processed data derived from primary databases, and composite databases that collect and filter data from multiple primary databases. Examples of specific biological databases are provided, including nucleic acid databases like GenBank, protein sequence databases like Swiss-Prot, protein structure database PDB, and metabolic pathway database KEGG. Details about the purpose and features of some of these major databases like GenBank, DDBJ, EMBL, Swiss-Prot, and PDB are outlined in the document.
Cool Informatics Tools and Services for Biomedical ResearchDavid Ruau
This document provides an overview of bioinformatics tools and services for analyzing big data in biomedical research. It discusses traditional bioinformatics tools, analyzing genomic data from microarrays and next-generation sequencing without and with code, interpreting results using protein interaction networks and pathways, tools for data storage, cleaning and visualization, and making research reproducible. Galaxy, R, and programming are presented as useful for automated, reproducible analysis of large genomic datasets.
Metabolic pathway mapping against KEGG, Reactome, HMDB and CPDBDinesh Barupal
This document describes various approaches for mapping detected metabolites to metabolic pathways using online databases and tools. It discusses obtaining KEGG identifiers for metabolites, using KEGG, Reactome, MetaboAnalyst and ConsensusPathDB to map identifiers to pathways and visualize pathways with overlays of mapped metabolites. It notes some metabolites may not have identifiers or map to pathways and emphasizes mapping identified more compounds than shown on pathway maps through enrichment analysis.
The document discusses biological databases. It begins by defining what a database is, including that it is a collection of related data organized in a way that allows information to be retrieved easily. It then discusses different types of biological databases, including those containing nucleotide sequences, protein sequences, 3D structures, gene expression data, and metabolic pathways. The rest of the document provides details on specific biological databases like GenBank, EMBL, DDBJ, and NCBI databases including Entrez. It emphasizes that biological data is heterogeneous, large in volume, dynamic and integrated across multiple databases.
The BioAssay Research Database (BARD) aims to enable scientists to utilize data from the Molecular Libraries Program Collection (MLPCN) to generate new hypotheses. BARD provides a platform for public data sharing and analysis through intuitive query and visualization tools accessible via a web portal or desktop client. BARD integrates data from multiple sources and centers, and aims to improve data annotation and standardization to enable more meaningful experiment descriptions and discovery. The project involves ongoing community engagement and development of new analytical tools through its open API and plugin framework.
The document discusses knowledge management of experimental data through the ISA ecosystem. It describes the ISA-tab format and software suite that allows annotation and curation of experimental metadata. As a use case, it analyzes a dataset on metabolite profiling from a study of fatty acid amide hydrolase knockout mice. The ISA tools can represent investigations and assays, convert data to standardized formats, and facilitate sharing and analysis of experimental data.
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 document discusses the key features and functions that an ideal scientific data management system should have. It should manage users, instruments, biological samples, experiments and related workflows. It should support standards, ontologies, data models and data exchange formats. The system should be accessible from any device and integrate with other software and external resources. It should support the full lifecycle of information, enable collaboration and knowledge generation from documents and data. It should also be prepared to handle large increases in data volumes.
Ontology Web Services for Semantic Applications Trish Whetzel
The document summarizes the Ontology Web Services provided by the National Center for Biomedical Ontology (NCBO) including the BioPortal Ontology Web services, NCBO Annotator Web service, and NCBO Resource Index Web service. These services allow programmatic access and traversal of ontologies, annotation of text with ontology terms, and searching of public biomedical data repositories indexed with ontology terms. The services aim to facilitate integration and interpretation of biomedical data on the Semantic Web.
Scratchpads in the Biodiversity Informatics LandscapeVince Smith
Roberts, D., Harman, K., Rycroft, S.D. & Smith, V.S. Stockholm Biodiversity Informatics Symposium 2008, Swedish Museum of Natural History, Stockholm, Sweden 1-4 December 2008.
Biological databases store and organize large amounts of biological data for research use. There are many types of biological databases that classify data by type, such as nucleotide sequences, protein sequences, genomes, protein structures, gene expression, and metabolic pathways. Databases can also be classified by their data source as primary databases containing experimental results or secondary databases that analyze primary database results. Database availability varies, with some publicly open and others proprietary. Common biological databases discussed include GenBank, UniProt, PDB, KEGG, and FlyBase.
This document discusses the ISA Commons project, which aims to facilitate sharing of life science experiments using a common structured representation. It does this by [1] using a format that can describe experiments across domains, [2] following community standards and norms, and [3] being implemented in curation and data sharing tools. The presentation outlines challenges around inconsistent reporting and many related standards, and describes how ISA Commons addresses these through its metadata tracking framework and software suite. This enables standardized experimental annotation and data sharing across a growing number of public resources and research groups.
Role of bioinformatics in life sciences researchAnshika Bansal
1. The document discusses bioinformatics and summarizes some of its key applications and tools. It describes how bioinformatics merges biology and computer science to solve biological problems by applying computational tools to molecular data.
2. It provides examples of common bioinformatics tasks like retrieving sequences from databases, comparing sequences, analyzing genes and proteins, and viewing 3D structures.
3. The document lists several popular databases for nucleotide sequences, protein sequences, literature, and other biological data. It also introduces common bioinformatics tools for tasks like sequence alignment, translation, and structure analysis.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk about BioThings API project at ISMB 2018 Chicago, as part of BD2K special session. BioThings API project provides a collection of high-performance APIs (MyGene.info, MyVariant.info, MyChem.info), an SDK for building a new biomedical API (BioThings SDK), and a JSON-LD and OpenAPI based solution for across-API interoperability and knowledge exploration.
1. This document provides a detailed protocol for performing GO and KEGG enrichment analysis on gene lists from rice (Oryza sativa).
2. It describes obtaining GO and KEGG annotations from public databases and an R package, and using the clusterProfiler package in R for enrichment analysis and visualization of results.
3. GO enrichment analysis using self-curated annotation files from rice databases identified 29 enriched GO terms, while KEGG enrichment analysis identified 11 enriched pathways.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk at NCI's CBIIT speaker series:
https://wiki.nci.nih.gov/display/CBIITSpeakers/2019/01/02/Jan+16%2C+Chunlei+Wu%2C+BioThings+API
A companion blog post: https://ncip.nci.nih.gov/blog/the-network-of-biothings/
See more details about BioThings project at http://biothings.io.
Bioinformatic Harvester is a software tool that acts as a meta search engine for genes and protein information. It collects and indexes data from 16 major bioinformatics databases and allows users to search across these databases simultaneously. Search results are displayed on a single HTML page and are ranked based on relevance. Users can query the system using terms like gene names, sequences, protein domains, and literature to retrieve integrated information from databases on genes and proteins.
Using ontologies to do integrative systems biologyChris Evelo
The document discusses using ontologies to integrate systems biology data. It describes typical steps in systems biology studies such as finding studies, processing data, integrating data, and combining data from multiple sources. Ontologies can help link information from different analysis techniques and combine data from many studies by capturing study metadata. The document advocates using standards like ISA-TAB and MAGE-TAB to capture study data and proposes using a generic study capture framework with modular components to integrate different types of 'omics data. Ontologies are needed for collaboration and to provide controlled vocabularies for annotation.
The document discusses various types of biological databases. It describes primary databases that contain original data, secondary databases that contain processed data derived from primary databases, and composite databases that collect and filter data from multiple primary databases. Examples of specific biological databases are provided, including nucleic acid databases like GenBank, protein sequence databases like Swiss-Prot, protein structure database PDB, and metabolic pathway database KEGG. Details about the purpose and features of some of these major databases like GenBank, DDBJ, EMBL, Swiss-Prot, and PDB are outlined in the document.
Cool Informatics Tools and Services for Biomedical ResearchDavid Ruau
This document provides an overview of bioinformatics tools and services for analyzing big data in biomedical research. It discusses traditional bioinformatics tools, analyzing genomic data from microarrays and next-generation sequencing without and with code, interpreting results using protein interaction networks and pathways, tools for data storage, cleaning and visualization, and making research reproducible. Galaxy, R, and programming are presented as useful for automated, reproducible analysis of large genomic datasets.
Metabolic pathway mapping against KEGG, Reactome, HMDB and CPDBDinesh Barupal
This document describes various approaches for mapping detected metabolites to metabolic pathways using online databases and tools. It discusses obtaining KEGG identifiers for metabolites, using KEGG, Reactome, MetaboAnalyst and ConsensusPathDB to map identifiers to pathways and visualize pathways with overlays of mapped metabolites. It notes some metabolites may not have identifiers or map to pathways and emphasizes mapping identified more compounds than shown on pathway maps through enrichment analysis.
The document discusses biological databases. It begins by defining what a database is, including that it is a collection of related data organized in a way that allows information to be retrieved easily. It then discusses different types of biological databases, including those containing nucleotide sequences, protein sequences, 3D structures, gene expression data, and metabolic pathways. The rest of the document provides details on specific biological databases like GenBank, EMBL, DDBJ, and NCBI databases including Entrez. It emphasizes that biological data is heterogeneous, large in volume, dynamic and integrated across multiple databases.
The BioAssay Research Database (BARD) aims to enable scientists to utilize data from the Molecular Libraries Program Collection (MLPCN) to generate new hypotheses. BARD provides a platform for public data sharing and analysis through intuitive query and visualization tools accessible via a web portal or desktop client. BARD integrates data from multiple sources and centers, and aims to improve data annotation and standardization to enable more meaningful experiment descriptions and discovery. The project involves ongoing community engagement and development of new analytical tools through its open API and plugin framework.
The document discusses knowledge management of experimental data through the ISA ecosystem. It describes the ISA-tab format and software suite that allows annotation and curation of experimental metadata. As a use case, it analyzes a dataset on metabolite profiling from a study of fatty acid amide hydrolase knockout mice. The ISA tools can represent investigations and assays, convert data to standardized formats, and facilitate sharing and analysis of experimental data.
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 document discusses the key features and functions that an ideal scientific data management system should have. It should manage users, instruments, biological samples, experiments and related workflows. It should support standards, ontologies, data models and data exchange formats. The system should be accessible from any device and integrate with other software and external resources. It should support the full lifecycle of information, enable collaboration and knowledge generation from documents and data. It should also be prepared to handle large increases in data volumes.
Ontology Web Services for Semantic Applications Trish Whetzel
The document summarizes the Ontology Web Services provided by the National Center for Biomedical Ontology (NCBO) including the BioPortal Ontology Web services, NCBO Annotator Web service, and NCBO Resource Index Web service. These services allow programmatic access and traversal of ontologies, annotation of text with ontology terms, and searching of public biomedical data repositories indexed with ontology terms. The services aim to facilitate integration and interpretation of biomedical data on the Semantic Web.
Scratchpads in the Biodiversity Informatics LandscapeVince Smith
Roberts, D., Harman, K., Rycroft, S.D. & Smith, V.S. Stockholm Biodiversity Informatics Symposium 2008, Swedish Museum of Natural History, Stockholm, Sweden 1-4 December 2008.
Biological databases store and organize large amounts of biological data for research use. There are many types of biological databases that classify data by type, such as nucleotide sequences, protein sequences, genomes, protein structures, gene expression, and metabolic pathways. Databases can also be classified by their data source as primary databases containing experimental results or secondary databases that analyze primary database results. Database availability varies, with some publicly open and others proprietary. Common biological databases discussed include GenBank, UniProt, PDB, KEGG, and FlyBase.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Pushing the limits of ePRTC: 100ns holdover for 100 days
Ismb2012_poster_cwu
1. : a community-driven customizable gene annotation portal
Chunlei Wu, Ian MacLeod, Andrew I. Su
cwu@scripps.edu, imacleod@scripps.edu, asu@scripps.edu
Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA
Candidate genes Testable
hypothesis
Gene databases are numerous and overlapping
http://www.ncbi.nlm.nih.gov/pubmed?term={{Symbol}}
Users can add new resources to BioGPS as “plugins”
Simply need a URL template:
http://string-db.org/newstring_cgi?...&identifier={{EnsemblGene}}
… and hundreds more …
http://www.genome.jp/dbget-bin/www_bget?hsa:{{EntrezGene}}
http://smart.embl-heidelberg.de/smart/show_motifs.pl?ID={{Uniprot}}
http://flybase.org/reports/{{FLYBASE}}.html
http://omim.org/entry/{{MIM}}
Users can customize their gene-report ”layout” ……
~ 30 types of gene-specific identifiers
BioGPS
BioGPS users contributed > 400 resources in plugin library
NCBI
Structural biologist PDB
PFAM
BioGPS
eQTL dbSNP
Why? Why?
Geneticist Discover resources by what’s popular among other users
Genome
Users MGI
Browser
Requests
BioGPS BioGPS users “like” a resource
Community
development
Expression KEGG by adding it into a custom layout, so
Resources
System Biologist that other users can discover popular
Time GeneCards resources they might miss.
Developers typically define the Development resources do not
gene-report view scale with increased users and
feature-requests
MyGene.Info: gene annotation web services
(Powers BioGPS gene query, now for public use)
BioGPS users: (up to Jul 8, 2012)
MyGene.Info provides simple-to-use REST web services to query/retrieve gene annotation
Queried 680k genes in last year data. It's designed with simplicity and performance emphasized.
Viewed 800k gene-reports in last year Gene query service: Gene annotation service
http://mygene.info/query?q=<query> http://mygene.info/gene/<geneid>
Signed up 5600 user accounts “user query” “gene id” “gene id” “a specific annotation/identifiers”
Saved 2200 layouts (>1300 users) Full query documentation at:
Added 400 plugins (>100 users)
http://mygene.info
Top 10 organizations:
Harvard Stanford http://biogps.org BioGPS iPhone App
NIH UCSF http://sulab.org/category/biogps
Scripps U Penn http://twitter.com/biogps
UCSD Wash U
MIT UNC