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Prezentace Guerrilla Readers na konferenci K21, únor 2009.
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Bgs120 debopriyo roy
Debopriyo Roy
Biochemical ontologies aim to capture and represent biochemical entities and the relations that exist between them in an accurate manner. A fundamental starting point is biochemical identity, but our current approach for generating identifiers is haphazard and consequently integrating data is error-prone. I will discuss plausible structure-based strategies for biochemical identity whether it be at molecular level or some part thereof (e.g. residues, collection of residues, atoms, collection of atoms, functional groups) such that identifiers may be generated in an automatic and curator/database independent manner. With structure-based identifiers in hand, we will be in a position to more accurately capture context-specific biochemical knowledge, such as how a set of residues in a binding site are involved in a chemical reaction including the fact that a key nitrogen atom must first be de-protonated. Thus, our current representation of biochemical knowledge may improve such that manual and automatic methods of bio-curation are substantially more accurate.
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Prezentace Guerrilla Readers na konferenci K21, únor 2009.
GR (R)Evoluci spousti...
GR (R)Evoluci spousti...
Guerrilla Readers
Bgs120 debopriyo roy
Bgs120 debopriyo roy
Debopriyo Roy
Biochemical ontologies aim to capture and represent biochemical entities and the relations that exist between them in an accurate manner. A fundamental starting point is biochemical identity, but our current approach for generating identifiers is haphazard and consequently integrating data is error-prone. I will discuss plausible structure-based strategies for biochemical identity whether it be at molecular level or some part thereof (e.g. residues, collection of residues, atoms, collection of atoms, functional groups) such that identifiers may be generated in an automatic and curator/database independent manner. With structure-based identifiers in hand, we will be in a position to more accurately capture context-specific biochemical knowledge, such as how a set of residues in a binding site are involved in a chemical reaction including the fact that a key nitrogen atom must first be de-protonated. Thus, our current representation of biochemical knowledge may improve such that manual and automatic methods of bio-curation are substantially more accurate.
Increasingly Accurate Representation of Biochemistry (v2)
Increasingly Accurate Representation of Biochemistry (v2)
Michel Dumontier
üYe çEkim SüReci DeğErlendirmesi
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AGENTS OF GOD
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Russian & English: Nastas Ltrs of Confirmation-Contributions
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Thomas Nastas
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery. The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
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Slides accompanying my talk at UFWH conference in Bangkok, Thailand. Topic: Slacktivism vs. Activism. Does a 'like' help those in need?
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Published comments on contributions of Nastas, in VC investment and program management.
Russian & English: Nastas Ltrs of Confirmation-Contributions
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Thomas Nastas
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery. The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
Model Organism Linked Data
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