An expert knowledge base on human performance and cognition was created by extracting information from scientific literature using natural language processing and pattern-based techniques. Over 3 million facts were extracted from abstracts and mapped to a hierarchical structure derived from Wikipedia. The knowledge base was deployed through a browsing tool called Scooner that allows users to navigate relationships between concepts. Further work is focused on improving knowledge base quality by normalizing entities, filtering assertions, and integrating related ontologies and vocabularies.
A knowledge capture framework for domain specific search systemsramakanz
This is the product roll out presentation at the AFRL on creating a focused knowledge base, search, and retrieval system for the domain of human performance and cognition.
Bioinformatics involves the analysis of biological information using computers and statistical techniques,
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences.
The sequence alignment is made between a known sequence and unknown sequence or between two unknown sequences. The known sequence is called reference sequence. The unknown sequence is called query sequence .
BLAST stands for Basic Local Alignment Search Tool. It addresses a fundamental problem in bioinformatics research. BLAST tool is used to compare a query sequence with a library or database of sequences.
In Bioinformatics, is an algorithm and program for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences.
BLAST was developed by stochastic model of Samuel Karlin and Stephen Altschul in 1990. They proposed “a method for estimating similarities between the known DNA sequence of one organism with that of another”.
A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query sequence) with a library or database of sequences and identify database sequences that resemble the query sequence above a certain threshold.
Arcomem training Topic Analysis Models beginnersarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
A knowledge capture framework for domain specific search systemsramakanz
This is the product roll out presentation at the AFRL on creating a focused knowledge base, search, and retrieval system for the domain of human performance and cognition.
Bioinformatics involves the analysis of biological information using computers and statistical techniques,
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences.
The sequence alignment is made between a known sequence and unknown sequence or between two unknown sequences. The known sequence is called reference sequence. The unknown sequence is called query sequence .
BLAST stands for Basic Local Alignment Search Tool. It addresses a fundamental problem in bioinformatics research. BLAST tool is used to compare a query sequence with a library or database of sequences.
In Bioinformatics, is an algorithm and program for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences.
BLAST was developed by stochastic model of Samuel Karlin and Stephen Altschul in 1990. They proposed “a method for estimating similarities between the known DNA sequence of one organism with that of another”.
A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query sequence) with a library or database of sequences and identify database sequences that resemble the query sequence above a certain threshold.
Arcomem training Topic Analysis Models beginnersarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
Connecting life sciences data at the European Bioinformatics InstituteConnected Data World
Tony Burdett's slides from his talk at Connected Data London. Tony is a Senior Software Engineer at The European Bioinformatics Institute. He presented the complexity of data at the EMBL-EBI and what is their solution to make sense of all this data.
Arcomem training Topic Analysis Models advancedarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
Bioinformatics may be defined as the field of science
in which biology, computer science, and information
technology merge to form a single discipline. Its ultimate
goal is to enable the discovery of new biological insights as
well as to create a global perspective from which unifying
principles in biology can be discerned by means of
bioinformatics tools for storing, retrieving, organizing and
analyzing biological data. Also most of these tools possess
very distinct features and capabilities making a direct
comparison difficult to be done. In this paper we propose
taxonomy for characterizing bioinformatics tools and briefly
surveys major bioinformatics tools under each categories.
Hopefully this study will stimulate other designers
and
experienced end users understand the details of particular
tool categories/tools, enabling them to make the best choices
for their particular research interests.
Information recovery is the recovery of things (objects, Web pages, archives, and so forth) that fulfill explicit conditions set in an ordinary articulation like query. While IR targets fulfilling a bit of client data need generally communicated in common language, information recovery targets figuring out which records contain the specific terms of the user queries.
Connecting life sciences data at the European Bioinformatics InstituteConnected Data World
Tony Burdett's slides from his talk at Connected Data London. Tony is a Senior Software Engineer at The European Bioinformatics Institute. He presented the complexity of data at the EMBL-EBI and what is their solution to make sense of all this data.
Arcomem training Topic Analysis Models advancedarcomem
This presentation on Topic Analysis Models is part of the ARCOMEM training curriculum. Feel free to roam around or contact us on Twitter via @arcomem to learn more about ARCOMEM training on archiving Social Media.
Bioinformatics may be defined as the field of science
in which biology, computer science, and information
technology merge to form a single discipline. Its ultimate
goal is to enable the discovery of new biological insights as
well as to create a global perspective from which unifying
principles in biology can be discerned by means of
bioinformatics tools for storing, retrieving, organizing and
analyzing biological data. Also most of these tools possess
very distinct features and capabilities making a direct
comparison difficult to be done. In this paper we propose
taxonomy for characterizing bioinformatics tools and briefly
surveys major bioinformatics tools under each categories.
Hopefully this study will stimulate other designers
and
experienced end users understand the details of particular
tool categories/tools, enabling them to make the best choices
for their particular research interests.
Information recovery is the recovery of things (objects, Web pages, archives, and so forth) that fulfill explicit conditions set in an ordinary articulation like query. While IR targets fulfilling a bit of client data need generally communicated in common language, information recovery targets figuring out which records contain the specific terms of the user queries.
Diversity and Depth: Implementing AI across many long tail domainsPaul Groth
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.
Biological literature mining - from information retrieval to biological disco...Lars Juhl Jensen
14th International Conference on Intelligent Systems for Molecular Biology, Tutorial, Fortaleza Conference Center, Fortaleza, Brazil, August 6-10, 2006
Data-knowledge transition zones within the biomedical research ecosystemMaryann Martone
Overview of the Neuroscience Information Framework and how it brings together data, in the form of distributed databases, and knowledge, in the form of ontologies to show the mapping of the dataspace and places where there are mismatches between data and knowledge.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
An Up-to-date Knowledge Base and Focused Exploration System for Human Performance and Cognition
1. An Up-to-date Knowledge Base and Focused Exploration System for Human Performance and Cognition AmitSheth LexisNexis Ohio Eminent Scholar Director, Kno.e.sis Center Wright State University RamakanthKavuluru Postdoctoral Research Scientist Kno.e.sis Center Thanks to Dr. Victor Chan for support and guidance HPC-KB team: Christopher Thomas, Wenbo Wang, Alan Smith, Paul Fultz, Delroy Cameron, Priti Parikh
2. Focused Knowledge Bases A knowledge base (KB) functions as a standalone reference for a particular domain of interest backend for knowledge-based search, browsing, and exploration of literature
3. What is a KB? “A body of knowledge describing a topic or domain of interest” categories or classes – Neurotransmitters, Disease individuals (instances of classes) Dopamine, Magnesium, Migraine roles (properties/predicates) – inhibits, is a, part of assertions (triples) Dopamine is a neurotransmitter Magnesium treats Migraine
4. Then, What are Ontologies? “Ontology is the basic structure or armature around which a knowledge base can be built” (Swartout and Tate, 1999) “An ontology is an explicit representation of a shared understanding of the important concepts in some domain of interest.” (Kalfoglou, 2001) So, mostly static blocks of well accepted and consensual knowledge
5. Ontologies in Life Sciences The National Center for Biomedical Ontology (NCBO) - Open Biomedical Ontologies (OBO) About 200 ontologies and 1.5 million terms Only part_of and is_a relations in the Gene Ontology Histolysis is_a positive regulation of cell size Requests for changes are expert reviewed before modifications
6. What about Emergent Knowledge, Richer Relationships? New scientific results and insights published everyday backed by experimentation PubMed: 18+ million articles; 1300 new per day Also, what about other predicates besides is_a and part_of (eg., UMLS Semantic Network of 54 predicates). Need a way of capturing and meaningfully utilizing this emerging knowledge
8. Steps in Creating the HPC-KB Carve a focused domain hierarchy out of Wikipedia Extract mentions of entities and relationships in the relevant scientific literature (Pubmed abstracts) to support non-hierarchical guidance. Map extracted entity mentions to concepts and extracted predicates to relationships to create the knowledge-base
9. Workflow Overview HPC keywords Doozer: Base Hierarchy from Wikipedia Focused Pattern based extraction SenseLab Neuroscience Ontologies Initial KB Creation Meta Knowledgebase PubMed Abstracts Knoesis: Parsing based NLP Triples Enrich Knowledge Base NLM: Rule based BKR Triples Final Knowledge Base
11. Triple Extraction Open Extraction No fixed number of predetermined entities and predicates At Knoesis – NLP (parsing and dependency trees) Supervised Extraction Predetermined set of entities and predicates At Knoesis – Pattern based extraction to connect entities in the base hierarchy using statistical techniques At NLM – NLP and rule based approaches
12. Mapping of Triples to Hierarchy Entities in both subject and object must contain at least one concept from the hierarchy to be mapped to the KB Preliminary synonyms based on anchor labels and page redirects in Wikipedia Prolactostatin redirects to Dopamine Predicates (verbs) and entities are subjected to stemming using Wordnet
18. Comments on Scooner “The ability to browse predications together with documents will likely reduce the cognitive load required for encountering interesting facts, both for novice users and domain experts.” – Thomas Rindflesch, Researcher in Biomedical Informatics, NLM. “Being able to keep track of multiple articles is a really nice tool to have, and it cuts down on time between jumping back and forth between articles” - Anonymous comment from an AFRL researcher
19. Next: Knexpace Automatic Updates Index new abstracts as they arrive Extract relationships as new abstracts arrive Periodically update indices for abstracts and triples Other Maintenance Admin interfaces Application software support
20. Improving the KB Quality & Filtering Adhere to a stricter schema Having a fixed number of predicates and a fixed range and domain for each predicate Ex: For the immunology and chemical warfare agents Predicate: activates Restricted Domain: Cytokines OR μRNA Restricted Range: Macrophages Also useful to directly launch queries of the form Question: ?x activates Macrophages Answer: TNF-α and IFN-γ
21. Normalize Entities and Predicates How do we find Bovine spongiform encephalopathy and mad cow disease are same (Use UMLS Metathesaurus! ) long term memory and long lasting memory are the same computationally (UMLS does not work) More complex similarities: HepG(2) cell line and Human Hepatoma G2 cells which textual forms map to the fixed set of predicates: Do modulates, regulates, stimulates all map to affects?(NLM expert collaboration & AFRL help) NLM tools: MetaMap, SemRep, and other lexical tools
22. Provenance and other meta data Original abstract PMIDs will be captured for each triple. Other data: authors, journal names How about other meta data for filtering: In Vitro / In Vivo If, In Vivo, which organism. If Mice, which type: Ames Dwarf Which techniques are used. ex: Flow Cytometry
23. New Knowledge Example VIP Peptide – increases – Catecholamine Biosynthesis Catecholamines – induce – β-adrenergic receptor activity β-adrenergic receptors – are involved – fear conditioning VIP Peptide – affects – fear conditioning In Cattle In Rats In Humans
24. Domain Specific Provenance For Immunology and Warfare Agent effects Which pathogen: Francisellatularensis Which Strains: U112, LVS, … What is measured: Cells (dendritic, macrophages, monocytes), Proteins, cytokines, chemokines Need to find preexisting taxonomies for organisms, techniques, pathogens; or need to build some and integrate The more the specificity, the more the KB quality
25. Better Ranking of Abstracts and Triples Use search phrases to fine tune ranking of abstracts and triples Just because the user clicked on neurogenesis, does not mean she wants to know everything about it. Predict which triples or abstracts the user might be more interested in the current search session. Show top-k entities in the result set to facilitate filtering based on top concepts Visualize networks of a set of browsed triples
26. Semantic Integration Famous OBO Ontologies (total 7 foundry ontologies) Gene Ontology PRotein Ontology Other domain specific OBO candidateontologies NCBI organismal classification Infectious Disease Human Disease (Tularemia found here, and also in SNOMED, & others too, what to choose for mapping?) Pathogen transmission
27. Semantic Integration, contd… Linked Open Drug Data DrugBank: drugs and drug targets (pathways, structures, pathways) Diseasome: disorders and disease-gene associations LinkedCT: Clinical trials Mendelian Inheritance Online MendelianInhertance in Animals (OMIA) Online Mendelian Inheritance in Man (OMIM) Different formats: owl, obo, rrf
Just say that knowledge bases are useful for two specific purposes.In the next slide talk about what exactly is a KB, what does it look like.
Emphasize the predicates are primary indicators of new knowledge.People are aware of concepts, but what is interesting is which predicates (if any) connect those concepts
The edges here show part_of and is_a relations: neuroscience is a subclass of science, while brain is part of the general area of cognitive science.So we do not model a strict ontology here.
Ncbi – national center for biotechnology informationObo – open biomedical ontologiesNcbo – natinal center for biomedical ontologySNOMED - Systematized Nomenclature of Medicine