Graph-Driven Features Extraction from Microarray Data
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A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles
ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles Andreas Hoppe and Hermann-Georg Holzhütter Charité University Medicine Berlin, Institute for Biochemistry, Computational Systems Biochemistry Group [email protected] Abstract Genome-wide transcript profiles are often the only available quantitative data for a particular perturbation of a cellular system and their interpretation with respect to the metabolism is a major challenge in systems biology, especially beyond on/off distinction of genes. We present a method that predicts activity changes of metabolic functions by scoring reference flux distributions based on relative transcript profiles, providing a ranked list of most regulated functions. Then, for each metabolic function, the involved genes are ranked upon how much they represent a specific regulation pattern. Compared with the naïve pathway-based approach, the reference modes can be chosen freely, and they represent full metabolic functions, thus, directly provide testable hypotheses for the metabolic study. In conclusion, the novel method provides promising functions for subsequent experimental elucidation together with outstanding associated genes, solely based on transcript profiles. 1998 ACM Subject Classification J.3 Life and Medical Sciences Keywords and phrases Metabolic network, expression profile, metabolic function Digital Object Identifier 10.4230/OASIcs.GCB.2012.1 1 Background The comprehensive study of the cell’s metabolism would include measuring metabolite concentrations, reaction fluxes, and enzyme activities on a large scale. Measuring fluxes is the most difficult part in this, for a recent assessment of techniques, see [31]. Although mass spectrometry allows to assess metabolite concentrations in a more comprehensive way, the larger the set of potential metabolites, the more difficult [8]. -
The Kyoto Encyclopedia of Genes and Genomes (KEGG)
Kyoto Encyclopedia of Genes and Genome Minoru Kanehisa Institute for Chemical Research, Kyoto University HFSPO Workshop, Strasbourg, November 18, 2016 The KEGG Databases Category Database Content PATHWAY KEGG pathway maps Systems information BRITE BRITE functional hierarchies MODULE KEGG modules KO (KEGG ORTHOLOGY) KO groups for functional orthologs Genomic information GENOME KEGG organisms, viruses and addendum GENES / SSDB Genes and proteins / sequence similarity COMPOUND Chemical compounds GLYCAN Glycans Chemical information REACTION / RCLASS Reactions / reaction classes ENZYME Enzyme nomenclature DISEASE Human diseases DRUG / DGROUP Drugs / drug groups Health information ENVIRON Health-related substances (KEGG MEDICUS) JAPIC Japanese drug labels DailyMed FDA drug labels 12 manually curated original DBs 3 DBs taken from outside sources and given original annotations (GENOME, GENES, ENZYME) 1 computationally generated DB (SSDB) 2 outside DBs (JAPIC, DailyMed) KEGG is widely used for functional interpretation and practical application of genome sequences and other high-throughput data KO PATHWAY GENOME BRITE DISEASE GENES MODULE DRUG Genome Molecular High-level Practical Metagenome functions functions applications Transcriptome etc. Metabolome Glycome etc. COMPOUND GLYCAN REACTION Funding Annual budget Period Funding source (USD) 1995-2010 Supported by 10+ grants from Ministry of Education, >2 M Japan Society for Promotion of Science (JSPS) and Japan Science and Technology Agency (JST) 2011-2013 Supported by National Bioscience Database Center 0.8 M (NBDC) of JST 2014-2016 Supported by NBDC 0.5 M 2017- ? 1995 KEGG website made freely available 1997 KEGG FTP site made freely available 2011 Plea to support KEGG KEGG FTP academic subscription introduced 1998 First commercial licensing Contingency Plan 1999 Pathway Solutions Inc. -
3 13437143.Pdf
Title Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones Imanishi, Tadashi; Itoh, Takeshi; Suzuki, Yutaka; O'Donovan, Claire; Fukuchi, Satoshi; Koyanagi, Kanako O.; Barrero, Roberto A.; Tamura, Takuro; Yamaguchi-Kabata, Yumi; Tanino, Motohiko; Yura, Kei; Miyazaki, Satoru; Ikeo, Kazuho; Homma, Keiichi; Kasprzyk, Arek; Nishikawa, Tetsuo; Hirakawa, Mika; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Ashurst, Jennifer; Jia, Libin; Nakao, Mitsuteru; Thomas, Michael A.; Mulder, Nicola; Karavidopoulou, Youla; Jin, Lihua; Kim, Sangsoo; Yasuda, Tomohiro; Lenhard, Boris; Eveno, Eric; Suzuki, Yoshiyuki; Yamasaki, Chisato; Takeda, Jun-ichi; Gough, Craig; Hilton, Phillip; Fujii, Yasuyuki; Sakai, Hiroaki; Tanaka, Susumu; Amid, Clara; Bellgard, Matthew; Bonaldo, Maria de Fatima; Bono, Hidemasa; Bromberg, Susan K.; Brookes, Anthony J.; Bruford, Elspeth; Carninci, Piero; Chelala, Claude; Couillault, Christine; Souza, Sandro J. de; Debily, Marie-Anne; Devignes, Marie-Dominique; Dubchak, Inna; Endo, Toshinori; Estreicher, Anne; Eyras, Eduardo; Fukami-Kobayashi, Kaoru; R. Gopinath, Gopal; Graudens, Esther; Hahn, Yoonsoo; Han, Michael; Han, Ze-Guang; Hanada, Kousuke; Hanaoka, Hideki; Harada, Erimi; Hashimoto, Katsuyuki; Hinz, Ursula; Hirai, Momoki; Hishiki, Teruyoshi; Hopkinson, Ian; Imbeaud, Sandrine; Inoko, Hidetoshi; Kanapin, Alexander; Kaneko, Yayoi; Kasukawa, Takeya; Kelso, Janet; Kersey, Author(s) Paul; Kikuno, Reiko; Kimura, Kouichi; Korn, Bernhard; Kuryshev, Vladimir; Makalowska, Izabela; Makino, Takashi; Mano, Shuhei; -
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. -
Molecular Biology for Computer Scientists
CHAPTER 1 Molecular Biology for Computer Scientists Lawrence Hunter “Computers are to biology what mathematics is to physics.” — Harold Morowitz One of the major challenges for computer scientists who wish to work in the domain of molecular biology is becoming conversant with the daunting intri- cacies of existing biological knowledge and its extensive technical vocabu- lary. Questions about the origin, function, and structure of living systems have been pursued by nearly all cultures throughout history, and the work of the last two generations has been particularly fruitful. The knowledge of liv- ing systems resulting from this research is far too detailed and complex for any one human to comprehend. An entire scientific career can be based in the study of a single biomolecule. Nevertheless, in the following pages, I attempt to provide enough background for a computer scientist to understand much of the biology discussed in this book. This chapter provides the briefest of overviews; I can only begin to convey the depth, variety, complexity and stunning beauty of the universe of living things. Much of what follows is not about molecular biology per se. In order to 2ARTIFICIAL INTELLIGENCE & MOLECULAR BIOLOGY explain what the molecules are doing, it is often necessary to use concepts involving, for example, cells, embryological development, or evolution. Bi- ology is frustratingly holistic. Events at one level can effect and be affected by events at very different levels of scale or time. Digesting a survey of the basic background material is a prerequisite for understanding the significance of the molecular biology that is described elsewhere in the book. -
Ontology-Based Methods for Analyzing Life Science Data
Habilitation a` Diriger des Recherches pr´esent´ee par Olivier Dameron Ontology-based methods for analyzing life science data Soutenue publiquement le 11 janvier 2016 devant le jury compos´ede Anita Burgun Professeur, Universit´eRen´eDescartes Paris Examinatrice Marie-Dominique Devignes Charg´eede recherches CNRS, LORIA Nancy Examinatrice Michel Dumontier Associate professor, Stanford University USA Rapporteur Christine Froidevaux Professeur, Universit´eParis Sud Rapporteure Fabien Gandon Directeur de recherches, Inria Sophia-Antipolis Rapporteur Anne Siegel Directrice de recherches CNRS, IRISA Rennes Examinatrice Alexandre Termier Professeur, Universit´ede Rennes 1 Examinateur 2 Contents 1 Introduction 9 1.1 Context ......................................... 10 1.2 Challenges . 11 1.3 Summary of the contributions . 14 1.4 Organization of the manuscript . 18 2 Reasoning based on hierarchies 21 2.1 Principle......................................... 21 2.1.1 RDF for describing data . 21 2.1.2 RDFS for describing types . 24 2.1.3 RDFS entailments . 26 2.1.4 Typical uses of RDFS entailments in life science . 26 2.1.5 Synthesis . 30 2.2 Case study: integrating diseases and pathways . 31 2.2.1 Context . 31 2.2.2 Objective . 32 2.2.3 Linking pathways and diseases using GO, KO and SNOMED-CT . 32 2.2.4 Querying associated diseases and pathways . 33 2.3 Methodology: Web services composition . 39 2.3.1 Context . 39 2.3.2 Objective . 40 2.3.3 Semantic compatibility of services parameters . 40 2.3.4 Algorithm for pairing services parameters . 40 2.4 Application: ontology-based query expansion with GO2PUB . 43 2.4.1 Context . 43 2.4.2 Objective . -
Genbank by Walter B
GenBank by Walter B. Goad o understand the significance of the information stored in memory—DNA—to the stuff of activity—proteins. The idea that GenBank, you need to know a little about molecular somehow the bases in DNA determine the amino acids in proteins genetics. What that field deals with is self-replication—the had been around for some time. In fact, George Gamow suggested in T process unique to life—and mutation and 1954, after learning about the structure proposed for DNA, that a recombination—the processes responsible for evolution-at the triplet of bases corresponded to an amino acid. That suggestion was fundamental level of the genes in DNA. This approach of working shown to be true, and by 1965 most of the genetic code had been from the blueprint, so to speak, of a living system is very powerful, deciphered. Also worked out in the ’60s were many details of what and studies of many other aspects of life—the process of learning, for Crick called the central dogma of molecular genetics—the now example—are now utilizing molecular genetics. firmly established fact that DNA is not translated directly to proteins Molecular genetics began in the early ’40s and was at first but is first transcribed to messenger RNA. This molecule, a nucleic controversial because many of the people involved had been trained acid like DNA, then serves as the template for protein synthesis. in the physical sciences rather than the biological sciences, and yet These great advances prompted a very distinguished molecular they were answering questions that biologists had been asking for geneticist to predict, in 1969, that biology was just about to end since years. -
The International Society for Computational Biology 10Th Anniversary Lawrence Hunter, Russ B
Message from ISCB The International Society for Computational Biology 10th Anniversary Lawrence Hunter, Russ B. Altman, Philip E. Bourne* Introduction training programs in bioinformatics or significant part of the original computational biology. By 1996, motivation for founding the Society PLoS Computational Biology is the however, high throughput molecular was to provide a stable financial home official journal of the International biology and the attendant need for for the ISMB conference. The first few Society for Computational Biology informatics had clearly arrived. In conferences were sufficiently successful (ISCB), a partnership that was formed addition to the founding of ISCB, 1996 to create a financial nest egg that was during the Journal’s conception in saw the sequencing of the first genome used each year to start the process of 2005. With ISCB being the only of a free-living organism (yeast) and planning and executing the next year’s international body representing Affymetrix’s release of its first meeting. Initially, relatively modest computational biologists, it made commercial DNA chip. checks were cut and sent from one perfect sense for PLoS Computational The hot topics in bioinformatics organizer to another informally. As the Biology to be closely affiliated. The circa 1996, at least as reflected by the size of these checks increased, the Society had to take more of a chance conference on Intelligent Systems for organizers (and their home than similar societies, choosing to step Molecular Biology (ISMB) at institutions) became increasingly away from an existing financially Washington University in St. Louis, uncomfortable exchanging them beneficial subscription journal to align included issues which have largely been informally, and decided that they with an open access publication as a solved (such as gene finding or needed an organization—thus, ISCB. -
Integrative Annotation of 21,037 Human Genes Validated by Full-Length Cdna Clones
Title Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones Imanishi, Tadashi; Itoh, Takeshi; Suzuki, Yutaka; O'Donovan, Claire; Fukuchi, Satoshi; Koyanagi, Kanako O.; Barrero, Roberto A.; Tamura, Takuro; Yamaguchi-Kabata, Yumi; Tanino, Motohiko; Yura, Kei; Miyazaki, Satoru; Ikeo, Kazuho; Homma, Keiichi; Kasprzyk, Arek; Nishikawa, Tetsuo; Hirakawa, Mika; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Ashurst, Jennifer; Jia, Libin; Nakao, Mitsuteru; Thomas, Michael A.; Mulder, Nicola; Karavidopoulou, Youla; Jin, Lihua; Kim, Sangsoo; Yasuda, Tomohiro; Lenhard, Boris; Eveno, Eric; Suzuki, Yoshiyuki; Yamasaki, Chisato; Takeda, Jun-ichi; Gough, Craig; Hilton, Phillip; Fujii, Yasuyuki; Sakai, Hiroaki; Tanaka, Susumu; Amid, Clara; Bellgard, Matthew; Bonaldo, Maria de Fatima; Bono, Hidemasa; Bromberg, Susan K.; Brookes, Anthony J.; Bruford, Elspeth; Carninci, Piero; Chelala, Claude; Couillault, Christine; Souza, Sandro J. de; Debily, Marie-Anne; Devignes, Marie-Dominique; Dubchak, Inna; Endo, Toshinori; Estreicher, Anne; Eyras, Eduardo; Fukami-Kobayashi, Kaoru; R. Gopinath, Gopal; Graudens, Esther; Hahn, Yoonsoo; Han, Michael; Han, Ze-Guang; Hanada, Kousuke; Hanaoka, Hideki; Harada, Erimi; Hashimoto, Katsuyuki; Hinz, Ursula; Hirai, Momoki; Hishiki, Teruyoshi; Hopkinson, Ian; Imbeaud, Sandrine; Inoko, Hidetoshi; Kanapin, Alexander; Kaneko, Yayoi; Kasukawa, Takeya; Kelso, Janet; Kersey, Author(s) Paul; Kikuno, Reiko; Kimura, Kouichi; Korn, Bernhard; Kuryshev, Vladimir; Makalowska, Izabela; Makino, Takashi; Mano, Shuhei; -
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. -
Scalable Approaches for Auditing the Completeness of Biomedical Ontologies
University of Kentucky UKnowledge Theses and Dissertations--Computer Science Computer Science 2021 Scalable Approaches for Auditing the Completeness of Biomedical Ontologies Fengbo Zheng University of Kentucky, [email protected] Author ORCID Identifier: https://orcid.org/0000-0001-5902-0186 Digital Object Identifier: https://doi.org/10.13023/etd.2021.128 Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Zheng, Fengbo, "Scalable Approaches for Auditing the Completeness of Biomedical Ontologies" (2021). Theses and Dissertations--Computer Science. 105. https://uknowledge.uky.edu/cs_etds/105 This Doctoral Dissertation is brought to you for free and open access by the Computer Science at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Computer Science by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. -
Development and Application of Ligand-Based Cheminformatics Tools for Drug Discovery from Natural Products
Development and application of ligand-based cheminformatics tools for drug discovery from natural products Entwicklung und Anwendung von ligandenbasierten Cheminformatik-Programmen für die Identifizierung von Arzneimitteln aus Naturstoffen INAUGURALDISSERTATION zur Erlangung des Doktorgrades der Fakultät für Chemie und Pharmazie der Albert-Ludwigs-Universität Freiburg im Breisgau vorgelegt von Kiran Kumar Telukunta aus Hyderabad, Indien Juli 2018 Dekan: Prof. Dr. Manfred Jung Universität Freiburg Institut für Pharmazeutische Wissenschaften Chemische Epigenetik Albertstraße 25 79104 Freiburg Vorsitzender: Prof. Dr. Stefan Weber des Promotionsausschusses Universität Freiburg Institut für Physikalische Chemie Physikalishe Chemie Albertstraße 21 79104 Freiburg Referent: Prof. Dr. Stefan Günther Universität Freiburg Institut für Pharmazeutische Wissenschaften Pharmazeutische Bioinformatik Hermann-Herder-Straße 9 79104 Freiburg Korreferent: Prof. Dr. Rolf Backofen Universität Freiburg Institut für Informatik Lehrstuhl für Bioinformatik Georges-Köhler-Allee 106 79110 Freiburg Drittprüfer: Prof. Dr. Andreas Bechthold Universität Freiburg Institut für Pharmazeutische Wissenschaften Pharmazeutische Biologie und Biotechnologie Stefan-Meier-Straße 19 79104 Freiburg Prüfungsdatum: 30 Aug 2018 Eidesstattliche Erklärung Hiermit erkläre ich, dass ich diese Arbeit allein und ausschließlich unter Nutzung der direkt oder sinngemäß gekennzeichneten Zitate geschrieben habe. Weiterhin versichere ich, dass diese Arbeit in keinem anderen Prüfungsverfahren eingereicht