An Ecosystem for Exploring, Analyzing, and Curating Mappings Across Pathway Databases
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces Cerevisiae
Metabolites 2013, 3, 1102-1117; doi:10.3390/metabo3041102 OPEN ACCESS metabolites ISSN 2218-1989 www.mdpi.com/journal/metabolites/ Article Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces cerevisiae Stefan Jenkins 1,2,3,*, Steven M. Fischer 2, Lily Chen 3 and Theodore R. Sana 2 1 Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA 2 Agilent Technologies, Life Sciences, Diagnostics and Applied Markets, Santa Clara, CA 95051, USA; E-Mails: [email protected] (S.M.F.); [email protected] (T.R.S.) 3 Biology Department, San Francisco State University, San Francisco, CA 94132, USA; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +1-650-922-5046; Fax: +1-510-486-4545. Received: 15 October 2013; in revised form: 20 November 2013 / Accepted: 25 November 2013 / Published: 6 December 2013 Abstract: Previous studies have shown that calcium stressed Saccharomyces cerevisiae, challenged with immunosuppressant drugs FK506 and Cyclosporin A, responds with comprehensive gene expression changes and attenuation of the generalized calcium stress response. Here, we describe a global metabolomics workflow for investigating the utility of tracking corresponding phenotypic changes. This was achieved by efficiently analyzing relative abundance differences between intracellular metabolite pools from wild-type and calcium stressed cultures, with and without prior immunosuppressant drugs exposure. We used pathway database content from WikiPathways and YeastCyc to facilitate the projection of our metabolomics profiling results onto biological pathways. A key challenge was to increase the coverage of the detected metabolites. This was achieved by applying both reverse phase (RP) and aqueous normal phase (ANP) chromatographic separations, as well as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources for detection in both ion polarities. -
And Macro-Level Network Metrics Unveils Top Communicative Gene Modules in Psoriasis
G C A T T A C G G C A T genes Article Using Micro- and Macro-Level Network Metrics Unveils Top Communicative Gene Modules in Psoriasis 1, 2 3 Reyhaneh Naderi y, Homa Saadati Mollaei , Arne Elofsson 3, , and Saman Hosseini Ashtiani * y 1 Department of Artificial Intelligence and Robotics, Faculty of Computer Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran; [email protected] 2 Department of Advanced Sciences and Technology, Islamic Azad University Tehran Medical Sciences, Tehran 1916893813, Iran; [email protected] 3 Department of Biochemistry and Biophysics and Science for Life Laboratory, Stockholm University, 106 91 Stockholm, Sweden; [email protected] * Correspondence: [email protected]; Tel.: +46-762623644 These authors contributed equally to this work and should be considered joint first authors. y Received: 9 July 2020; Accepted: 6 August 2020; Published: 10 August 2020 Abstract: (1) Background: Psoriasis is a multifactorial chronic inflammatory disorder of the skin, with significant morbidity, characterized by hyperproliferation of the epidermis. Even though psoriasis’ etiology is not fully understood, it is believed to be multifactorial, with numerous key components. (2) Methods: In order to cast light on the complex molecular interactions in psoriasis vulgaris at both protein–protein interactions and transcriptomics levels, we studied a set of microarray gene expression analyses consisting of 170 paired lesional and non-lesional samples. Afterwards, a network analysis was conducted on the protein–protein interaction network of differentially expressed genes based on micro- and macro-level network metrics at a systemic level standpoint. (3) Results: We found 17 top communicative genes, all of which were experimentally proven to be pivotal in psoriasis, which were identified in two modules, namely the cell cycle and immune system. -
Biological Pathways
Biological pathways Bing Zhang Department of Biomedical Informatics Vanderbilt University [email protected] Biological pathway A biological pathway is a series of actions among molecules in a cell that leads to a certain product or a change in a cell. Different types of biological pathways Signal transduction pathways Gene regulation pathways Metabolic pathways 2 Applied Bioinformatics, Spring 2011 Outline Pathway databases Pathway assembly and editing Pathway mapping and enrichment analysis 3 Applied Bioinformatics, Spring 2011 Selected pathway databases KEGG Kyoto Encyclopedia of Genes and Genomes http://www.genome.jp/kegg/pathway.html Reactome Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute http://www.reactome.org/ WikiPathways University of Maastricht and UCSF http://www.wikipathways.org/ 4 Applied Bioinformatics, Spring 2011 KEGG: data model Molecular building blocks KEGG GENES: genes and proteins generated by genome sequencing projects KEGG ORTHOLOGY: orthology (KO) groups KEGG COMPOUND: small molecules KEGG REACTIONS: biochemical reactions KEGG PATHWAY: pathway maps Created in a general way to be applicable to all organisms, in terms of the orthologs defined by KO groups Organism-specific pathways can be generated by converting KO groups to gene identifiers in a given organism 5 Applied Bioinformatics, Spring 2011 KEGG: TCA cycle 6 Applied Bioinformatics, Spring 2011 Reactome: data model Entities -
Confirmation of Pathogenic Mechanisms by SARS-Cov-2–Host
Messina et al. Cell Death and Disease (2021) 12:788 https://doi.org/10.1038/s41419-021-03881-8 Cell Death & Disease ARTICLE Open Access Looking for pathways related to COVID-19: confirmation of pathogenic mechanisms by SARS-CoV-2–host interactome Francesco Messina 1, Emanuela Giombini1, Chiara Montaldo1, Ashish Arunkumar Sharma2, Antonio Zoccoli3, Rafick-Pierre Sekaly2, Franco Locatelli4, Alimuddin Zumla5, Markus Maeurer6,7, Maria R. Capobianchi1, Francesco Nicola Lauria1 and Giuseppe Ippolito 1 Abstract In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level, but the mechanisms of interaction between host and SARS-CoV-2, determining the grade of COVID-19 severity, are still unknown. We provide a network analysis on protein–protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred, applying an explorative algorithm (Random Walk with Restart, RWR) triggered by 28 proteins of SARS-CoV-2. The analysis of PPI allowed to estimate the distribution of SARS-CoV-2 proteins in the host cell. Interactome built around one single viral protein allowed to define a different response, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, the network-based approach highlighted a possible direct action of ORF3a and NS7b to enhancing Bradykinin Storm. This network-based representation of SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; clinical outcomes. -
Reactome Pathway Analysis
Fabregat et al. BMC Bioinformatics (2017) 18:142 DOI 10.1186/s12859-017-1559-2 SOFTWARE Open Access Reactome pathway analysis: a high- performance in-memory approach Antonio Fabregat1,2, Konstantinos Sidiropoulos1, Guilherme Viteri1, Oscar Forner1, Pablo Marin-Garcia3,4, Vicente Arnau5,6, Peter D’Eustachio7, Lincoln Stein8,9 and Henning Hermjakob1,10* Abstract Background: Reactome aims to provide bioinformatics tools for visualisation, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modelling, systems biology and education. Pathway analysis methods have a broad range of applications in physiological and biomedical research; one of the main problems, from the analysis methods performance point of view, is the constantly increasing size of the data samples. Results: Here, we present a new high-performance in-memory implementation of the well-established over- representation analysis method. To achieve the target, the over-representation analysis method is divided in four different steps and, for each of them, specific data structures are used to improve performance and minimise the memory footprint. The first step, finding out whether an identifier in the user’s sample corresponds to an entity in Reactome, is addressed using a radix tree as a lookup table. The second step, modelling the proteins, chemicals, their orthologous in other species and their composition in complexes and sets, is addressed with a graph. The third and fourth steps, that aggregate the results and calculate the statistics, are solved with a double-linked tree. Conclusion: Through the use of highly optimised, in-memory data structures and algorithms, Reactome has achieved a stable, high performance pathway analysis service, enabling the analysis of genome-wide datasets within seconds, allowing interactive exploration and analysis of high throughput data. -
Biological Pathways Exchange Language Level 3, Release Version 1 Documentation
BioPAX – Biological Pathways Exchange Language Level 3, Release Version 1 Documentation BioPAX Release, July 2010. The BioPAX data exchange format is the joint work of the BioPAX workgroup and Level 3 builds on the work of Level 2 and Level 1. BioPAX Level 3 input from: Mirit Aladjem, Ozgun Babur, Gary D. Bader, Michael Blinov, Burk Braun, Michelle Carrillo, Michael P. Cary, Kei-Hoi Cheung, Julio Collado-Vides, Dan Corwin, Emek Demir, Peter D'Eustachio, Ken Fukuda, Marc Gillespie, Li Gong, Gopal Gopinathrao, Nan Guo, Peter Hornbeck, Michael Hucka, Olivier Hubaut, Geeta Joshi- Tope, Peter Karp, Shiva Krupa, Christian Lemer, Joanne Luciano, Irma Martinez-Flores, Zheng Li, David Merberg, Huaiyu Mi, Ion Moraru, Nicolas Le Novere, Elgar Pichler, Suzanne Paley, Monica Penaloza- Spinola, Victoria Petri, Elgar Pichler, Alex Pico, Harsha Rajasimha, Ranjani Ramakrishnan, Dean Ravenscroft, Jonathan Rees, Liya Ren, Oliver Ruebenacker, Alan Ruttenberg, Matthias Samwald, Chris Sander, Frank Schacherer, Carl Schaefer, James Schaff, Nigam Shah, Andrea Splendiani, Paul Thomas, Imre Vastrik, Ryan Whaley, Edgar Wingender, Guanming Wu, Jeremy Zucker BioPAX Level 2 input from: Mirit Aladjem, Gary D. Bader, Ewan Birney, Michael P. Cary, Dan Corwin, Kam Dahlquist, Emek Demir, Peter D'Eustachio, Ken Fukuda, Frank Gibbons, Marc Gillespie, Michael Hucka, Geeta Joshi-Tope, David Kane, Peter Karp, Christian Lemer, Joanne Luciano, Elgar Pichler, Eric Neumann, Suzanne Paley, Harsha Rajasimha, Jonathan Rees, Alan Ruttenberg, Andrey Rzhetsky, Chris Sander, Frank Schacherer, -
Post-Graduate Diploma Program in Personalized Genomic Medicine” for Skill Development (DBT Sponsored Scheme)
UNIVERSITY OF MYSORE Syllabus for “Post-graduate Diploma Program in Personalized Genomic Medicine” For Skill Development (DBT Sponsored Scheme) FCBCS-CAGP SYSTEM Department of Studies in Genetics and Genomics University of Mysore Manasagangotri, Mysuru – 570 006 2019-20 1 PREAMBLE: The Information and potential use of genomic discoveries are no longer issues left for scientists and medical professionals to handle, but have become ones for the public at large. Rarely a day passes without genomics related story reported in the media. The proposed diploma program is designed to provide advanced knowledge dissemination in the field of genome sciences, applications and laboratory skills needed for molecular diagnostics and precision medicine procedures conducted in a clinical or research environment. The program is intended for those individuals who wish to enhance their laboratory expertise and knowledge in molecular-based methods. Precision medicine has the potential to fundamentally change how health care is practiced, but requires a trained health care workforce that understands the complexities of this field. One important component of precision medicine is the use of an individual’s genomic information to offer targeted treatment, tailored to the individual. Our course aims to provide participants with advanced knowledge of genomics, an overview of the clinical applications of genomic medicine, the skills to evaluate the clinical validity and utility of new tests, and an appreciation of the associated ethical and social issues inherent in this field. The course is geared towards individuals with a background in the biological sciences and a basic understanding of genetics. It is designed to be succinct and clinically focused, offering both conceptual and practical information about real-world applications of genomics. -
Signaling in the Innate Immune Response
Signaling in the innate immune response The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Kim, Dennis H. “Signaling in the Innate Immune Response.” WormBook (December 2015): 1–51 © 2015 WormBook As Published http://dx.doi.org/10.1895/wormbook.1.83.2 Publisher WormBook Version Final published version Citable link http://hdl.handle.net/1721.1/109292 Terms of Use Creative Commons Attribution Detailed Terms http://creativecommons.org/licenses/by/2.5/ Signaling in the innate immune response Dennis H. Kim1§ and Jonathan J. Ewbank2§ 1Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 2 Centre d’Immunologie de Marseille-Luminy, Aix Marseille Université UM2, INSERM, U1104, CNRS UMR7280, 13288 Marseille, France. Edited by Iva Greenwald Last revised September 16, 2015 §To whom correspondence should be addressed. E-mail: [email protected] or [email protected] WormBook Early Online, published on December 22, 2015 as doi: 10.1895/wormbook.1.83.2. 1 1. Introduction The maintenance of cellular and organismal homeostasis in the face of changes in the environment is essential for survival. Pathogenic microorganisms represent one type of environmental challenge. Plants and animals have developed immune systems to counter the threat of infection. The innate immune system is an ancient system of host defense against microbial pathogens present across a very broad range of species. Genetic studies of innate immunity in Drosophila and mammals have revealed an evolutionary conservation of signaling mechanisms (Medzhitov and Janeway, 1998), which has been corroborated in part by the study of innate immunity in Caenorhabditis elegans. -
TERRA Regulate the Transcriptional Landscape of Pluripotent Cells
RESEARCH ARTICLE TERRA regulate the transcriptional landscape of pluripotent cells through TRF1-dependent recruitment of PRC2 Rosa Marı´aMario´ n1†, Juan J Montero1†, Isabel Lo´ pez de Silanes1, Osvaldo Gran˜ a-Castro2, Paula Martı´nez1, Stefan Schoeftner1‡§, Jose´ Alejandro Palacios-Fa´ brega1#, Maria A Blasco1* 1Telomeres and Telomerase Group, Molecular Oncology Program, Spanish National Cancer Centre (CNIO), Madrid, Spain; 2Bioinformatics Unit, Structural Biology Program, Spanish National Cancer Centre (CNIO), Madrid, Spain Abstract The mechanisms that regulate pluripotency are still largely unknown. Here, we show that Telomere Repeat Binding Factor 1 (TRF1), a component of the shelterin complex, regulates the genome-wide binding of polycomb and polycomb H3K27me3 repressive marks to pluripotency genes, thereby exerting vast epigenetic changes that contribute to the maintenance of mouse ES *For correspondence: cells in a naı¨ve state. We further show that TRF1 mediates these effects by regulating TERRA, the [email protected] lncRNAs transcribed from telomeres. We find that TERRAs are enriched at polycomb and stem cell † These authors contributed genes in pluripotent cells and that TRF1 abrogation results in increased TERRA levels and in higher equally to this work TERRA binding to those genes, coincidental with the induction of cell-fate programs and the loss of Present address: ‡Genomic the naı¨ve state. These results are consistent with a model in which TRF1-dependent changes in Stability Unit, Laboratorio TERRA levels modulate polycomb -
The Scope of Pathway Curation Data Community
1/25/2019 Biocuration of genes and pathways Biocuration involves the creation of a user-friendly narrative of biological information—based on review, analysis and systematic organization of data—using manual and semi-automated methods. Involving the Research Community in Biocuration of Genes and Pathways Sushma Naithani Department of Botany and Plant Pathology Oregon State University [email protected] Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 Plant Reactome in the grand scheme of An example of a curated rice reference pathway in genomics science the Plant Reactome Data generation Knowledgebase Plant’s response to biotic stimuli: Fungi and Bacteria • Sequence data • Mining • Proteomes • Synthesis • Genotyping • Visualization Handling • Phenotype • Cyberinfrastructure • Analysis • Storage • Annotation • Metadata Data impacts • Hypothesis • Translational research Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 Plant Reactome: an open resource for the The scope of pathway curation data community Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 Plant and Animal Genome XXVII, San Diego, Jan 15, 2019 1 1/25/2019 Biocuration is one of the bottlenecks in making Involving the community in biocuration genomic data FAIR Finding a common framework to depict pathways PubMed search results for anthocyanin biosynthesis 600 500 Year 2018 - 499 items Dec • Expertise 400 300 • Time 200 Numberofpublications -
An Analysis of Differences in Biological Pathway Resources
An Analysis of Differences In Biological Pathway Resources Lucy L. Wang, John H. Gennari, and Neil F. Abernethy Department of Biomedical Informatics and Medical Education, University of Washington Seattle, Washington 98195 Email: [email protected], [email protected], [email protected] Abstract—Integrating content from multiple biological bilistically combine protein interactions from various pathway resources is necessary to fully exploit pathway pathway databases into merged networks [11]. These knowledge for the benefit of biology and medicine. Dif- tools improve querying of multiple resource, and pave ferences in content, representation, coverage, and more occur between databases, and are challenges to resource the way towards more comprehensive network models merging. We introduce a typology of representational of human biological processes. differences between pathway resources and give exam- Some work has also been done in inter-resource ples using several databases: BioCyc, KEGG, PANTHER pathways, and Reactome. We also detect and quantify comparison, quantifying the overlap between different annotation mismatches between HumanCyc and Reactome. databases [12–15]. These comparison studies emphasize The typology of mismatches can be used to guide entity and differences in entity membership in pathways and differ- relationship alignment between these databases, helping us ing counts of unique entities and pathways, but do not identify and understand deficiencies in our knowledge, and focus on cross-resource entity alignment. Existing tools allowing -
Research Journal of Pharmaceutical, Biological and Chemical Sciences
ISSN: 0975-8585 Research Journal of Pharmaceutical, Biological and Chemical Sciences Pathvisio++: An Interactive Web Server for Analyzing Metabolic Pathways. Udayakumar Mani*, Krishna Nishand M, Raghu Ram G, and Sai Mukund Ramakrishnan. Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA UNIVERSITY, Tanjore-613402, Tamilnadu, India. ABSTRACT Metabolic Pathways represents organized information about genes, proteins and metabolites. Wikipathways is a pathway database designed and managed by BigCat which contains both metabolic and proteomic pathways. The pathways in Wikipathways are of GPML format which is unique to itself. Wikipathways is an extension of GenMAPP pathway collection.Pathvisio is the only software designed to interpret and analyse GPML files. Pathways can be directly edited from a java applet editor where you can draw genes, proteins and their interactions like in any popular drawing tool. It is a static interface which shows only the pictorial representation of the pathways.Pathvisio++ is a highly interactive web based server which improves the functionality of Pathvisio, making it highly user friendly and efficient tool for analysing pathways. It is designed using XML, PHP, MySQL, JavaScript, HTML, Ajax, Perl, Bio Perl, HTML Maps and Apache server integrated with the WAMP server.It has many features like JavaScript viewer for visualization of pathways, ontologies for the genes involved in the pathways, modifying cellular location an export the pathways as annotated table .Pathvisio++ webserver can be browsed at http://scbt.sastra.edu/pathvisio . Keywords : pathways,regulation, GenMAPP, GPML, Ontologies, small molecule, the PHP GD. *Corresponding author January – February 2017 RJPBCS 8(1) Page No. 31 ISSN: 0975-8585 INTRODUCTION Pathways are represented as networks which provide intuitive views of the myriad of interactions.