Metrics for the Human Proteome Project 2016: Progress On
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A High-Stringency Blueprint of the Human Proteome
Providence St. Joseph Health Providence St. Joseph Health Digital Commons Articles, Abstracts, and Reports 10-16-2020 A high-stringency blueprint of the human proteome. Subash Adhikari Edouard C Nice Eric W Deutsch Institute for Systems Biology, Seattle, WA, USA. Lydie Lane Gilbert S Omenn See next page for additional authors Follow this and additional works at: https://digitalcommons.psjhealth.org/publications Part of the Genetics and Genomics Commons Recommended Citation Adhikari, Subash; Nice, Edouard C; Deutsch, Eric W; Lane, Lydie; Omenn, Gilbert S; Pennington, Stephen R; Paik, Young-Ki; Overall, Christopher M; Corrales, Fernando J; Cristea, Ileana M; Van Eyk, Jennifer E; Uhlén, Mathias; Lindskog, Cecilia; Chan, Daniel W; Bairoch, Amos; Waddington, James C; Justice, Joshua L; LaBaer, Joshua; Rodriguez, Henry; He, Fuchu; Kostrzewa, Markus; Ping, Peipei; Gundry, Rebekah L; Stewart, Peter; Srivastava, Sanjeeva; Srivastava, Sudhir; Nogueira, Fabio C S; Domont, Gilberto B; Vandenbrouck, Yves; Lam, Maggie P Y; Wennersten, Sara; Vizcaino, Juan Antonio; Wilkins, Marc; Schwenk, Jochen M; Lundberg, Emma; Bandeira, Nuno; Marko-Varga, Gyorgy; Weintraub, Susan T; Pineau, Charles; Kusebauch, Ulrike; Moritz, Robert L; Ahn, Seong Beom; Palmblad, Magnus; Snyder, Michael P; Aebersold, Ruedi; and Baker, Mark S, "A high-stringency blueprint of the human proteome." (2020). Articles, Abstracts, and Reports. 3832. https://digitalcommons.psjhealth.org/publications/3832 This Article is brought to you for free and open access by Providence St. Joseph Health -
3De8d416-B844-4E9a-B3fb-A2e883a4083f 11119
Edinburgh Research Explorer Last rolls of the yoyo: Assessing the human canonical protein count Citation for published version: Southan, C 2017, 'Last rolls of the yoyo: Assessing the human canonical protein count', F1000Research, vol. 6, pp. 448+. https://doi.org/10.12688/f1000research.11119.1 Digital Object Identifier (DOI): 10.12688/f1000research.11119.1 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: F1000Research Publisher Rights Statement: This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately -
Study of Conditions for the Emergence of Cellular Communication Using Self-Adaptive Multi-Agent Systems Sebastien Maignan
Study of conditions for the emergence of cellular communication using self-adaptive multi-agent systems Sebastien Maignan To cite this version: Sebastien Maignan. Study of conditions for the emergence of cellular communication using self- adaptive multi-agent systems. Artificial Intelligence [cs.AI]. Université Paul Sabatier - Toulouse III, 2018. English. NNT : 2018TOU30094. tel-02094368 HAL Id: tel-02094368 https://tel.archives-ouvertes.fr/tel-02094368 Submitted on 9 Apr 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Délivré par l'Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier) Sébastien Maignan Le 30 août 2018 Study of conditions for the emergence of cellular communication using self-adaptive multi-agent systems École doctorale et discipline ou spécialité ED MITT : Domaine STIC : Intelligence Artificielle Unité de recherche Institut de Recherche en Informatique de Toulouse Directrice(s) ou Directeur(s) de Thèse Pierre Glize, Carole Bernon Jury Marie BEURTON-AIMAR Maître de Conférences, HdR, Université de Bordeaux Rapporteur Vincent -
The Nextprot Knowledgebase in 2020
D328–D334 Nucleic Acids Research, 2020, Vol. 48, Database issue Published online 14 November 2019 doi: 10.1093/nar/gkz995 The neXtProt knowledgebase in 2020: data, tools and usability improvements Monique Zahn-Zabal1, Pierre-Andre´ Michel1, Alain Gateau1,Fred´ eric´ Nikitin1, Mathieu Schaeffer1,2, Estelle Audot1, Pascale Gaudet 1, Paula D. Duek1, Daniel Teixeira1, Valentine Rech de Laval1,2,3, Kasun Samarasinghe1,2,AmosBairoch1,2 and Lydie Lane1,2,* 1CALIPHO group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland, 2Department of microbiology and molecular medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland and 3Haute ecole´ specialis´ ee´ de Suisse occidentale, Haute Ecole de Gestion de Geneve,` Carouge, Switzerland Received September 11, 2019; Revised October 10, 2019; Editorial Decision October 11, 2019; Accepted October 18, 2019 ABSTRACT post-translational modifications (PTMs), as well as peptide identified in mass spectrometry experiments and epitopes The neXtProt knowledgebase (https://www.nextprot. recognized by antibodies have been integrated from a num- org) is an integrative resource providing both data ber of resources. By doing so, neXtProt extends the contents on human protein and the tools to explore these. of UniProtKB/Swiss-Prot (2) to provide a more compre- In order to provide comprehensive and up-to-date hensive data set. data, we evaluate and add new data sets. We describe However, data alone is not sufficient for scientists to the incorporation of three new data sets that provide comprehend complex information rapidly. For this reason, expression, function, protein-protein binary interac- neXtProt organizes the information concerning an entry in tion, post-translational modifications (PTM) and vari- several views, with interactive viewers that allow the user to ant information. -
PROTEOMICS the Human Proteome Takes the Spotlight
RESEARCH HIGHLIGHTS PROTEOMICS The human proteome takes the spotlight Two papers report mass spectrometry– big data. “We then thought, include some surpris- based draft maps of the human proteome ‘What is a potentially good ing findings. For example, and provide broadly accessible resources. illustration for the utility Kuster’s team found protein For years, members of the proteomics of such a database?’” says evidence for 430 long inter- community have been trying to garner sup- Kuster. “We very quickly genic noncoding RNAs, port for a large-scale project to exhaustively got to the idea, ‘Why don’t which have been thought map the normal human proteome, including we try to put together the not to be translated into pro- identifying all post-translational modifica- human proteome?’” tein. Pandey’s team refined tions and protein-protein interactions and The two groups took the annotations of 808 genes providing targeted mass spectrometry assays slightly different strategies and also found evidence and antibodies for all human proteins. But a towards this common goal. for the translation of many Nik Spencer/Nature Publishing Group Publishing Nik Spencer/Nature lack of consensus on how to exactly define Pandey’s lab examined 30 noncoding RNAs and pseu- Two groups provide mass the proteome, how to carry out such a mis- normal tissues, including spectrometry evidence for dogenes. sion and whether the technology is ready has adult and fetal tissues, as ~90% of the human proteome. Obtaining evidence for not so far convinced any funding agencies to well as primary hematopoi- the last roughly 10% of pro- fund on such an ambitious project. -
The Chromosome-Centric Human Proteome Project for Cataloging Proteins Encoded in the Genome
CORRESPONDENCE The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome To the Editor: utility for biological and disease studies. Table 1 Features of salient genes on The Chromosome-Centric Human With development of new tools for in- chromosomes 13 and 17 Proteome Project (C-HPP) aims to define depth characterization of the transcriptome Genea AST nsSNPs the full set of proteins encoded in each and proteome, the HPP is well positioned Chromosome 13 chromosome through development of a to have a strategic role in addressing the BRCA2 3 54 standardized approach for analyzing the complexity of human phenotypes. With this RB1 2 3 massive proteomic data sets currently being in mind, the HUPO has organized national IRS2 1 3 generated from dedicated efforts of national chromosome teams that will collaborate and international teams. The initial goal with well-established laboratories building Chromosome 17 of the C-HPP is to identify at least one complementary proteotypic peptides, BRCA1 24 24 representative protein encoded by each of antibodies and informatics resources. ERBB2 6 13 the approximately 20,300 human genes1,2. An important C-HPP goal is to encourage TP53 14 5 aEnsembl protein and AST information can be found at The proteins will be characterized for tissue capture and open sharing of proteomic http://www.ensembl.org/Homo_sapiens/. localization and major isoforms, including data sets from diverse samples to enhance AST, alternative splicing transcript; nsSNP, nonsyno- mous single-nucleotide polyphorphism assembled from post-translational modifications (PTMs), a gene- and chromosome-centric display data from the 1000 Genomes Projects. -
AP Biology: Chemistry B Mcgraw Hill AP Biology 2014-15 Contents
AP Biology: Chemistry B McGraw Hill AP Biology 2014-15 Contents 1 Carbohydrate 1 1.1 Structure .................................................. 1 1.2 Monosaccharides ............................................. 2 1.2.1 Classification of monosaccharides ................................ 2 1.2.2 Ring-straight chain isomerism .................................. 3 1.2.3 Use in living organisms ...................................... 3 1.3 Disaccharides ............................................... 3 1.4 Nutrition .................................................. 4 1.4.1 Classification ........................................... 5 1.5 Metabolism ................................................ 5 1.5.1 Catabolism ............................................ 5 1.6 Carbohydrate chemistry .......................................... 5 1.7 See also .................................................. 6 1.8 References ................................................. 6 1.9 External links ............................................... 7 2 Lipid 8 2.1 Categories of lipids ............................................ 8 2.1.1 Fatty acids ............................................. 8 2.1.2 Glycerolipids ........................................... 9 2.1.3 Glycerophospholipids ....................................... 9 2.1.4 Sphingolipids ........................................... 9 2.1.5 Sterol lipids ............................................ 10 2.1.6 Prenol lipids ............................................ 10 2.1.7 Saccharolipids .......................................... -
Sparqling Nextprot Data
SPARQLing neXtProt data SWAT4HCLS, Edinburgh, United Kingdom Monique Zahn www.sib.swiss Overview 01 Introduction to neXtProt 02 Data model 03 SPARQLing in neXtProt 04 Summary neXtProt – the SIB knowledgebase on human proteins https://www.nextprot.org/ Data sources COMING SOON : “We stand on the shoulders of giants.” Improved coverage through data integration Data on human proteins https://www.nextprot.org/entry/NX_P01308/ Views Types of data (1) https://www.nextprot.org/entry/NX_P01308/ Free text Structured Types of data (2) https://www.nextprot.org/entry/NX_P01308/sequence Positional Overview 01 Introduction to neXtProt 02 Data model 03 SPARQLing in neXtProt 04 Summary Data model https://www.nextprot.org/help/data-model Single interoperable model (RDF) Types of data Structured Positional Free text Distinguishing features 3 5 2 1 4 Overview 01 Introduction to neXtProt 02 Data model 03 SPARQLing in neXtProt 04 Summary SPARQL user interfaces https://www.nextprot.org/ 1 2 3 SPARQL endpoint : https://api.nextprot.org/sparql (SERVICE https://sparql.nextprot.org) neXtProt Advanced Search Find answers to complex questions: 1. Proteins whose genes are on chromosome 13 and are associated with a disease 2. Proteins with at least one variant of the types "A->R" or "R->A“ 3. Proteins with alternative acetylation or Ubl conjugation (SUMO or Ubiquitin) at the same positions 4. Proteins with at least two antibodies available from Human Protein Atlas that have associated tissue expression annotations from immunohistochemistry studies These queries cannot -
Converting Nextprot Into Linked Data and Nanopublications
Converting neXtProt into Linked Data and nanopublications Editor(s): Name Surname, University, Country Solicited review(s): Name Surname, University, Country Open review(s): Name Surname, University, Country Christine Chichester*a1, Oliver Karch*b, Pascale Gaudeta, Lydie Lanea, Barend Monsc, and Amos Bairocha a CALIPHO group, Swiss Institute of Bioinformatics, CMU 1 rue Michel Serve, 1211 Geneva 4, Switzerland b Biomarker Technologies, Discovery Bioinformatics, Merck Serono, Frankfurter Str. 250, 64271 Darmstadt, Germany c Netherlands Bioinformatics Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Abstract. The development of Linked Data provides the opportunity for databases to supply extensive volumes of biological data, information, and knowledge in a machine interpretable format to make previously isolated data silos interoperable. To increase ease of use, often databases incorporate annotations from several different resources. Linked Data can overcome many formatting and identifier issues that prevent data interoperability, but the extensive cross incorporation of annotations between databases makes the tracking of provenance in open, decentralized systems especially important. With the diversity of published data, provenance information becomes critical to providing reliable and trustworthy services to scientists. The nanopublication system addresses many of these challenges. We have developed the neXtProt Linked Data by serializing in RDF/XML annotations specific to neXtProt and started employing the nanopublication model to give appropriate attribution to all data. Specifically, a use case demonstrates the handling of post-translational modification (PTM) data modeled as nanopublications to illustrate the how the different levels of provenance and data quality thresholds can be captured in this model. Keywords: biological database, linked data, semantic web, nanopublication, post-translation modification 1 Corresponding author. -
Is It Time for Cognitive Bioinformatics?
g in Geno nin m i ic M s ta & a P Lisitsa et al., J Data Mining Genomics Proteomics 2015, 6:2 D r f o Journal of o t e l DOI: 10.4172/2153-0602.1000173 o a m n r i c u s o J ISSN: 2153-0602 Data Mining in Genomics & Proteomics Review Article Open Access Is it Time for Cognitive Bioinformatics? Andrey Lisitsa1,2*, Elizabeth Stewart2,3, Eugene Kolker2-5 1The Russian Human Proteome Organization (RHUPO), Institute of Biomedical Chemistry, Moscow, Russian Federation 2Data Enabled Life Sciences Alliance (DELSA Global), Moscow, Russian Federation 3Bioinformatics and High-Throughput Data Analysis Laboratory, Seattle Children’s Research Institute, Seattle, WA, USA 4Predictive Analytics, Seattle Children’s Hospital, Seattle, WA, USA 5Departments of Biomedical Informatics & Medical Education and Pediatrics, University of Washington, Seattle, WA, USA Abstract The concept of cognitive bioinformatics has been proposed for structuring of knowledge in the field of molecular biology. While cognitive science is considered as “thinking about the process of thinking”, cognitive bioinformatics strives to capture the process of thought and analysis as applied to the challenging intersection of diverse fields such as biology, informatics, and computer science collectively known as bioinformatics. Ten years ago cognitive bioinformatics was introduced as a model of the analysis performed by scientists working with molecular biology and biomedical web resources. At present, the concept of cognitive bioinformatics can be examined in the context of the opportunities represented by the information “data deluge” of life sciences technologies. The unbalanced nature of accumulating information along with some challenges poses currently intractable problems for researchers. -
Proteomics and Metabolomics: the Final Frontier of Nutrition Research 71
SIGHT AND LIFE | VOL. 29(1) | 2015 PROTEOMICS AND METABOLOMICS: THE FINAL FRONTIER OF NUTRITION RESEARCH 71 Proteomics and Metabolomics: The Final Frontier of Nutrition Research Richard D Semba RNA editing, RNA splicing, post-translational modifications, and Wilmer Eye Institute, Johns Hopkins University School protein degradation; the proteome does not strictly reflect the of Medicine, Baltimore, Maryland, USA genome. Proteins function as enzymes, hormones, receptors, immune mediators, structure, transporters, and modulators of cell communication and signaling. The metabolome consists Introduction of amino acids, amines, peptides, sugars, oligonucleotides, ke- Revolutionary new technologies allow us to penetrate scientific tones, aldehydes, lipids, steroids, vitamins, and other molecules. frontiers and open vast new territories for discovery. In astrono- These metabolites reflect intrinsic chemical processes in cells my, the Hubble Space Telescope has facilitated an unprecedent- as well as environmental exposures such as diet and gut micro- ed view outwards, beyond our galaxy. Wherever the telescope is bial flora. The current Human Metabolome Database contains directed, scientists are making exciting new observations of the more than 40,000 entries7 – a number that is expected to grow deep universe. Another revolution is taking place in two fields quickly in the future. of “omics” research: proteomics and metabolomics. In contrast, The goals of proteomics include the detection of the diver- this view is directed inwards, towards the complexity of biologi- sity of proteins, their quantity, their isoforms, and the localiza- cal processes in living organisms. Proteomics is the study of the tion and interactions of proteins. The goals of metabolomics structure and function of proteins expressed by an organism. -
How Many Human Proteoforms Are There?
PERSPECTIVE PUBLISHED ONLINE: 14 FEBRUARY 2018 | DOI: 10.1038/NCHEMBIO.2576 How many human proteoforms are there? Ruedi Aebersold1, Jeffrey N Agar2, I Jonathan Amster3 , Mark S Baker4 , Carolyn R Bertozzi5, Emily S Boja6, Catherine E Costello7, Benjamin F Cravatt8 , Catherine Fenselau9, Benjamin A Garcia10, Ying Ge11,12, Jeremy Gunawardena13, Ronald C Hendrickson14, Paul J Hergenrother15, Christian G Huber16 , Alexander R Ivanov2, Ole N Jensen17, Michael C Jewett18, Neil L Kelleher19* , Laura L Kiessling20 , Nevan J Krogan21, Martin R Larsen17, Joseph A Loo22 , Rachel R Ogorzalek Loo22, Emma Lundberg23,24, Michael J MacCoss25, Parag Mallick5, Vamsi K Mootha13, Milan Mrksich18, Tom W Muir26, Steven M Patrie19, James J Pesavento27 , Sharon J Pitteri5 , Henry Rodriguez6, Alan Saghatelian28, Wendy Sandoval29, Hartmut Schlüter30 , Salvatore Sechi31, Sarah A Slavoff32, Lloyd M Smith12,33, Michael P Snyder24, Paul M Thomas19 , Mathias Uhlén34, Jennifer E Van Eyk35, Marc Vidal36, David R Walt37, Forest M White38, Evan R Williams39, Therese Wohlschlager16, Vicki H Wysocki40, Nathan A Yates41, Nicolas L Young42 & Bing Zhang42 Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous ques- tions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry–based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease.