The Sixth Annual Biopathways Meeting
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Proquest Dissertations
Automated learning of protein involvement in pathogenesis using integrated queries Eithon Cadag A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2009 Program Authorized to Offer Degree: Department of Medical Education and Biomedical Informatics UMI Number: 3394276 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI Dissertation Publishing UMI 3394276 Copyright 2010 by ProQuest LLC. All rights reserved. This edition of the work is protected against unauthorized copying under Title 17, United States Code. uest ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Eithon Cadag and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: Reading Committee: (SjLt KJ. £U*t~ Peter Tgffczy-Hornoch In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this dissertation is allowable only for scholarly purposes, consistent with "fair use" as prescribed in the U.S. -
Trancep: Predicting Transmembrane Transport Proteins Using Composition, Evolutionary, and Positional Information
bioRxiv preprint doi: https://doi.org/10.1101/293159; this version posted April 2, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. TranCEP: Predicting transmembrane transport proteins using composition, evolutionary, and positional information Munira Alballa1, Faizah Aplop2, Gregory Butler1,3* 1 Department of Computer Science and Software Engineering, Concordia University, Montr´eal, Qu´ebec, Canada 2 School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, Malaysia 3 Centre for Structural and Functional Genomics, Concordia University, Montr´eal,Qu´ebec, Canada * [email protected] Abstract Transporters mediate the movement of compounds across the membranes that separate the cell from its environment, and across inner membranes surrounding cellular compartments. It is estimated that one third of a proteome consists of membrane proteins, and many of these are transport proteins. Given the increase in the number of genomes being sequenced, there is a need for computation tools that predict the substrates which are transported by the transmembrane transport proteins. In this paper, we present TranCEP, a predictor of the type of substrate transported by a transmembrane transport protein. TranCEP combines the traditional use of the amino acid composition of the protein, with evolutionary information captured in a multiple sequence alignment, and restriction to important positions of the alignment that play a role in determining specificity of the protein. Our experimental results show that TranCEP significantly outperforms the state of the art. -
Genome Informatics 4–8 September 2002, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
Comparative and Functional Genomics Comp Funct Genom 2003; 4: 509–514. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.300 Feature Meeting Highlights: Genome Informatics 4–8 September 2002, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK Jo Wixon1* and Jennifer Ashurst2 1MRC UK HGMP-RC, Hinxton, Cambridge CB10 1SB, UK 2The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK *Correspondence to: Abstract Jo Wixon, MRC UK HGMP-RC, Hinxton, Cambridge CB10 We bring you the highlights of the second Joint Cold Spring Harbor Laboratory 1SB, UK. and Wellcome Trust ‘Genome Informatics’ Conference, organized by Ewan Birney, E-mail: [email protected] Suzanna Lewis and Lincoln Stein. There were sessions on in silico data discovery, comparative genomics, annotation pipelines, functional genomics and integrative biology. The conference included a keynote address by Sydney Brenner, who was awarded the 2002 Nobel Prize in Physiology or Medicine (jointly with John Sulston and H. Robert Horvitz) a month later. Copyright 2003 John Wiley & Sons, Ltd. In silico data discovery background set was genes which had a log ratio of ∼0 in liver. Their approach found 17 of 17 known In the first of two sessions on this topic, Naoya promoters with a specificity of 17/28. None of the Hata (Cold Spring Harbor Laboratory, USA) sites they identified was located downstream of a spoke about motif searching for tissue specific TSS and all showed an excess in the foreground promoters. The first step in the process is to sample compared to the background sample. -
Microblogging the ISMB: a New Approach to Conference Reporting
Message from ISCB Microblogging the ISMB: A New Approach to Conference Reporting Neil Saunders1*, Pedro Beltra˜o2, Lars Jensen3, Daniel Jurczak4, Roland Krause5, Michael Kuhn6, Shirley Wu7 1 School of Molecular and Microbial Sciences, University of Queensland, St. Lucia, Brisbane, Queensland, Australia, 2 Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California, United States of America, 3 Novo Nordisk Foundation Center for Protein Research, Panum Institute, Copenhagen, Denmark, 4 Department of Bioinformatics, University of Applied Sciences, Hagenberg, Freistadt, Austria, 5 Max-Planck-Institute for Molecular Genetics, Berlin, Germany, 6 European Molecular Biology Laboratory, Heidelberg, Germany, 7 Stanford Medical Informatics, Stanford University, Stanford, California, United States of America Cameron Neylon entitled FriendFeed for Claire Fraser-Liggett opened the meeting Scientists: What, Why, and How? (http:// with a review of metagenomics and an blog.openwetware.org/scienceintheopen/ introduction to the human microbiome 2008/06/12/friendfeed-for-scientists-what- project (http://friendfeed.com/search?q = why-and-how/) for an introduction. room%3Aismb-2008+microbiome+OR+ We—a group of science bloggers, most fraser). The subsequent Q&A session of whom met in person for the first time at covered many of the exciting challenges The International Conference on Intel- ISMB 2008—found FriendFeed a remark- for those working in this field. Clearly, ligent Systems for Molecular Biology -
Towards a Knowledge Graph for Science
Towards a Knowledge Graph for Science Invited Article∗ Sören Auer Viktor Kovtun Manuel Prinz TIB Leibniz Information Centre for L3S Research Centre, Leibniz TIB Leibniz Information Centre for Science and Technology and L3S University of Hannover Science and Technology Research Centre at University of Hannover, Germany Hannover, Germany Hannover [email protected] [email protected] Hannover, Germany [email protected] Anna Kasprzik Markus Stocker TIB Leibniz Information Centre for TIB Leibniz Information Centre for Science and Technology Science and Technology Hannover, Germany Hannover, Germany [email protected] [email protected] ABSTRACT KEYWORDS The document-centric workflows in science have reached (or al- Knowledge Graph, Science and Technology, Research Infrastructure, ready exceeded) the limits of adequacy. This is emphasized by Libraries, Information Science recent discussions on the increasing proliferation of scientific lit- ACM Reference Format: erature and the reproducibility crisis. This presents an opportu- Sören Auer, Viktor Kovtun, Manuel Prinz, Anna Kasprzik, and Markus nity to rethink the dominant paradigm of document-centric schol- Stocker. 2018. Towards a Knowledge Graph for Science: Invited Article. arly information communication and transform it into knowledge- In WIMS ’18: 8th International Conference on Web Intelligence, Mining and based information flows by representing and expressing informa- Semantics, June 25–27, 2018, Novi Sad, Serbia. ACM, New York, NY, USA, tion through semantically rich, interlinked knowledge graphs. At 6 pages. https://doi.org/10.1145/3227609.3227689 the core of knowledge-based information flows is the creation and evolution of information models that establish a common under- 1 INTRODUCTION standing of information communicated between stakeholders as The communication of scholarly information is document-centric. -
Biocuration 2016 - Posters
Biocuration 2016 - Posters Source: http://www.sib.swiss/events/biocuration2016/posters 1 RAM: A standards-based database for extracting and analyzing disease-specified concepts from the multitude of biomedical resources Jinmeng Jia and Tieliu Shi Each year, millions of people around world suffer from the consequence of the misdiagnosis and ineffective treatment of various disease, especially those intractable diseases and rare diseases. Integration of various data related to human diseases help us not only for identifying drug targets, connecting genetic variations of phenotypes and understanding molecular pathways relevant to novel treatment, but also for coupling clinical care and biomedical researches. To this end, we built the Rare disease Annotation & Medicine (RAM) standards-based database which can provide reference to map and extract disease-specified information from multitude of biomedical resources such as free text articles in MEDLINE and Electronic Medical Records (EMRs). RAM integrates disease-specified concepts from ICD-9, ICD-10, SNOMED-CT and MeSH (http://www.nlm.nih.gov/mesh/MBrowser.html) extracted from the Unified Medical Language System (UMLS) based on the UMLS Concept Unique Identifiers for each Disease Term. We also integrated phenotypes from OMIM for each disease term, which link underlying mechanisms and clinical observation. Moreover, we used disease-manifestation (D-M) pairs from existing biomedical ontologies as prior knowledge to automatically recognize D-M-specific syntactic patterns from full text articles in MEDLINE. Considering that most of the record-based disease information in public databases are textual format, we extracted disease terms and their related biomedical descriptive phrases from Online Mendelian Inheritance in Man (OMIM), National Organization for Rare Disorders (NORD) and Orphanet using UMLS Thesaurus. -
Gearing up to Handle the Mosaic Nature of Life in the Quest for Orthologs. Kristoffer Forslund
The Jackson Laboratory The Mouseion at the JAXlibrary Faculty Research 2018 Faculty Research 1-15-2018 Gearing up to handle the mosaic nature of life in the quest for orthologs. Kristoffer Forslund Cecile Pereira Salvador Capella-Gutierrez Alan Sousa da Silva Adrian Altenhoff See next page for additional authors Follow this and additional works at: https://mouseion.jax.org/stfb2018 Part of the Life Sciences Commons, and the Medicine and Health Sciences Commons Recommended Citation Forslund, Kristoffer; Pereira, Cecile; Capella-Gutierrez, Salvador; Sousa da Silva, Alan; Altenhoff, Adrian; Huerta-Cepas, Jaime; Muffato, Matthieu; Patricio, Mateus; Vandepoele, Klaas; Ebersberger, Ingo; Blake, Judith A.; Fernández Breis, Jesualdo Tomás; Orthologs Consortium, The Quest for; Boeckmann, Brigitte; Gabaldón, Toni; Sonnhammer, Erik; Dessimoz, Christophe; and Lewis, Suzanna, "Gearing up to handle the mosaic nature of life in the quest for orthologs." (2018). Faculty Research 2018. 25. https://mouseion.jax.org/stfb2018/25 This Article is brought to you for free and open access by the Faculty Research at The ousM eion at the JAXlibrary. It has been accepted for inclusion in Faculty Research 2018 by an authorized administrator of The ousM eion at the JAXlibrary. For more information, please contact [email protected]. Authors Kristoffer Forslund, Cecile Pereira, Salvador Capella-Gutierrez, Alan Sousa da Silva, Adrian Altenhoff, Jaime Huerta-Cepas, Matthieu Muffato, Mateus Patricio, Klaas Vandepoele, Ingo Ebersberger, Judith A. Blake, Jesualdo Tomás -
ISMB 99 August 6 – 10, 1999 Heidelberg, Germany the Seventh
______________________________________ Welcome to ISMB 99 August 6 – 10, 1999 Heidelberg, Germany The Seventh International Conference on Intelligent Systems for Molecular Biology ______________________________________ Final Program and Detailed Schedule Friday, August 6, 1999 Tutorial Day The tutorials will take place in the following rooms: 8:30 – 12:30 (Coffee break around 10:30) Tutorial #1 Trübnersaal Piere Baldi Probabilistic graphical models Tutorial #2 Robert-Schumann-Zimmer Douglas L. Brutlag Bioinformatics and Molecular Biology Tutorial #3 Ballsaal Martin Reese The challenge of annotating a complete eukaryotic genome: A case study in Drosophila melanogaster Tutorial #4 Gustav-Mahler-Zimmer Tandy Warnow Computational and statistical Junhyong Kim challenges involved in reconstructing evolutionary trees Tutorial #5 Sebastian-Münster-Saal Thomas Werner The biology and bioinformatics of regulatory regions in genomes Lunch (on this day served in "Grosser Saal" on the ground floor) 13:30 – 17:30 (Coffee break around 15:30) Tutorial #6 Sebastian-Münster-Saal Rob Miller EST Clustering Alan Christoffels Winston Hide Tutorial #7 Trübnersaal Kevin Karplus Getting the most out of hidden Markov Melissa Cline models Christian Barrett Tutorial #8 Robert-Schumann-Zimmer Arthur Lesk Sequence-structure relationships and evolutionary structure changes in proteins Tutorial #9 Gustav-Mahler-Zimmer David States PERL abstractions for databases and Brian Dunford distributed computing Shore Tutorial # 10 Ballsaal Zoltan Szallasi Genetic network analysis -
The Evaluation of Ontologies: Editorial Review Vs
The Evaluation of Ontologies: Editorial Review vs. Democratic Ranking Barry Smith Department of Philosophy, Center of Excellence in Bioinformatics and Life Sciences, and National Center for Biomedical Ontology University at Buffalo from Proceedings of InterOntology 2008 (Tokyo, Japan, 26-27 February 2008), 127-138. ABSTRACT. Increasingly, the high throughput technologies used by biomedical researchers are bringing about a situation in which large bodies of data are being described using controlled structured vocabularies—also known as ontologies—in order to support the integration and analysis of this data. Annotation of data by means of ontologies is already contributing in significant ways to the cumulation of scientific knowledge and, prospectively, to the applicability of cross-domain algorithmic reasoning in support of scientific advance. This very success, however, has led to a proliferation of ontologies of varying scope and quality. We define one strategy for achieving quality assurance of ontologies—a plan of action already adopted by a large community of collaborating ontologists—which consists in subjecting ontologies to a process of peer review analogous to that which is applied to scientific journal articles. 1 From OBO to the OBO Foundry Our topic here is the use of ontologies to support scientific research, especially in the domains of biology and biomedicine. In 2001, Open Biomedical Ontologies (OBO) was created by Michael Ashburner and Suzanna Lewis as an umbrella body for the developers of such ontologies in the domain of the life sciences, applying the key principles underlying the success of the Gene Ontology (GO) [GOC 2006], namely, that ontologies be (a) open, (b) orthogonal, (c) instantiated in a well-specified syntax, and such as (d) to share a common space of identifiers [Ashburner et al. -
Challenges for Ontology Repositories and Applications to Biomedicine & Agronomy
Position paper – Keynote SIMBig 2017 – September 2017, Lima, Peru Challenges for ontology repositories and applications to biomedicine & agronomy Clement Jonquet Laboratory of Informatics, Robotics, and Microelectronics of Montpellier (LIRMM), University of Montpellier & CNRS, France & Center for BioMedical Informatics Research (BMIR), Stanford University, USA [email protected] (ORCID: 0000-0002-2404-1582) Abstract 1 Introduction The explosion of the number of ontologies The Semantic Web produces many vocabularies and vocabularies available in the Semantic and ontologies to represent and annotate any kind Web makes ontology libraries and reposi- of data. However, those ontologies are spread out, tories mandatory to find and use them. in different formats, of different size, with differ- Their functionalities span from simple on- ent structures and from overlapping domains. The tology listing with more or less of metada- scientific community has always been interested ta description to portals with advanced on- tology-based services: browse, search, vis- in designing common platforms to list and some- ualization, metrics, annotation, etc. Ontol- time host and serve ontologies, align them, and ogy libraries and repositories are usually enable their (re)use (Ding and Fensel, 2001; developed to address certain needs and Hartmann et al., 2009; D’Aquin and Noy, 2012; , communities. BioPortal, the ontology re- 1995). These platforms range from simple ontol- pository built by the US National Center ogy listings or libraries with structured metadata, for Biomedical Ontologies BioPortal relies to advanced repositories (or portals) which fea- on a domain independent technology al- ture a variety of services for multiple types of ready reused in several projects from bio- semantic resources (ontologies, vocabularies, medicine to agronomy and earth sciences. -
Interactive Knowledge Capture in the New Millennium: How the Semantic Web Changed Everything
To appear in the Special Issue for the 25th Anniversary the Knowledge Engineering Review, 2011. Interactive Knowledge Capture in the New Millennium: How the Semantic Web Changed Everything Yolanda Gil USC Information Sciences Institute [email protected] Last updated: January 10, 2011 Abstract The Semantic Web has radically changed the landscape of knowledge acquisition research. It used to be the case that a single user would edit a local knowledge base, that the user would have domain expertise to add to the system, and that the system would have a centralized knowledge base and reasoner. The world surrounding knowledge‐rich systems changed drastically with the advent of the Web, and many of the original assumptions were no longer a given. Those assumptions had to be revisited and addressed in combination with new challenges that were put forward. Knowledge‐rich systems today are distributed, have many users with different degrees of expertise, and integrate many shared knowledge sources of varying quality. Recent work in interactive knowledge capture includes new and exciting research on collaborative knowledge sharing, collecting knowledge from web volunteers, and capturing knowledge provenance. 1. Introduction For this special anniversary issue of the Knowledge Engineering Review, I prepared a personal perspective on recent research in the area of interactive knowledge capture. My research interest has always been human‐computer collaboration, in particular how to assist people in performing complex, knowledge‐rich tasks that cannot be -
Ontology-Driven Pathway Data Integration
©Copyright 2019 Lucy Lu Wang Ontology-driven pathway data integration Lucy Lu Wang A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2019 Reading Committee: John H. Gennari, Chair Neil F. Abernethy Paul K. Crane Program Authorized to Offer Degree: Biomedical & Health Informatics University of Washington Abstract Ontology-driven pathway data integration Lucy Lu Wang Chair of the Supervisory Committee: Graduate Program Director & Associate Professor John H. Gennari Biomedical Informatics and Medical Education Biological pathways are useful tools for understanding human physiology and disease pathogenesis. Pathway analysis can be used to detect genes and functions associated with complex disease pheno- types. When performing pathway analysis, researchers take advantage of multiple pathway datasets, combining pathways from different pathway databases. Pathways from different databases do not eas- ily inter-operate, and the resulting combined pathway dataset can suffer from redundancy or reduced interpretability. Ontologies have been used to organize pathway data and eliminate redundancy. I generated clus- ters of semantically similar pathways by mapping pathways from seven databases to classes of one such ontology, the Pathway Ontology (PW). I then produced a typology of differences between pathways by summarizing the differences in content and knowledge representation between databases. Using the typology, I optimized an entity and graph-based network alignment algorithm for aligning pathways between databases. The algorithm was applied to clusters of semantically similar pathways to generate normalized pathways for each PW class. These normalized pathways were used to produce normal- ized gene sets for gene set enrichment analysis (GSEA). I evaluated these normalized gene sets against baseline gene sets in GSEA using four public gene expression datasets.