Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Meghana Chitale"'
Publikováno v:
Department of Biological Sciences Faculty Publications
Scientific Reports
Scientific Reports
Reconstructing metabolic and signaling pathways is an effective way of interpreting a genome sequence. A challenge in a pathway reconstruction is that often genes in a pathway cannot be easily found, reflecting current imperfect information of the ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4139a0eec893374fbe307c5021921b3f
Publikováno v:
Bioinformatics
Motivation: Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f67f183b1b544e965bb64e62ae171c0
https://doi.org/10.1093/bioinformatics/bts398
https://doi.org/10.1093/bioinformatics/bts398
Publikováno v:
Nature Precedings
Motivation: Importance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c209ff738cd953aefeab9fdcda20fdf1
https://doi.org/10.1093/bioinformatics/btp309
https://doi.org/10.1093/bioinformatics/btp309
Publikováno v:
Bioinformatics (Oxford, England). 31(2)
Summary : Protein function prediction (PFP) is an automated function prediction method that predicts Gene Ontology (GO) annotations for a protein sequence using distantly related sequences and contextual associations of GO terms. Extended similarity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b26fcf003ac2e27d87bece8ce41b892
https://pubmed.ncbi.nlm.nih.gov/25273111
https://pubmed.ncbi.nlm.nih.gov/25273111
Autor:
Daisuke Kihara, Leec Sael, Juan Esquivel-Rodríguez, Mingjie Tang, Kean Ming Tan, Meghana Chitale, Xin Lu Tan
Publikováno v:
Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data
GRAPHICAL MODELS FOR PROTEIN FUNCTION AND STRUCTURE PREDICTION MINGJIE TANG,1,† KEAN MING TAN,2,† XIN LU TAN,2 LEE SAEL,1,3 MEGHANA CHITALE,1 JUAN ESQUIVEL-RODRIGUEZ,1 and DAISUKE KIHARA1,3 1Department of Computer Science, Purdue University, West
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::594544ce1cf5b7ee5bbfaa702a1082fe
https://doi.org/10.1002/9781118617151.ch09
https://doi.org/10.1002/9781118617151.ch09
Autor:
Christine A. Orengo, Liang Lan, Daniel W. A. Buchan, Jeffrey M. Yunes, Alberto Paccanaro, Yannick Mahlich, Enrico Lavezzo, Patricia C. Babbitt, Domenico Cozzetto, Cedric Landerer, Jari Björne, Esmeralda Vicedo, Robert Rentzsch, Rajendra Joshi, Hagit Shatkay, Nives Škunca, Zheng Wang, Tal Ronnen Oron, Ingolf Sommer, Amos Marc Bairoch, Mark Heron, Panče Panov, Daisuke Kihara, Wyatt T. Clark, Michael J.E. Sternberg, Steven E. Brenner, Sašo Džeroski, Burkhard Rost, Christian Schaefer, Karin Verspoor, Harshal Inamdar, Tapio Salakoski, Meghana Chitale, Alfonso E. Romero, Julian Gough, Fran Supek, Olivier Lichtarge, Dominik Achten, Serkan Erdin, Michael Kiening, Petri Törönen, Avik Datta, Iddo Friedberg, Thomas A. Hopf, Liisa Holm, Rita Casadio, Asa Ben-Hur, Tatjana Braun, Sean D. Mooney, Marco Falda, Kiley Graim, Michal Linial, Alexandra M. Schnoes, Christopher S. Funk, Rebecca Kaßner, Patrik Koskinen, Nemanja Djuric, Paolo Fontana, Predrag Radivojac, Tobias Wittkop, Kevin Bryson, Maximilian Hecht, Susanna Repo, Haixuan Yang, Artem Sokolov, Prajwal Bhat, Tobias Hamp, Jianlin Cheng, Mark N. Wass, Gaurav Pandey, Michael L Souza, Damiano Piovesan, Ameet Talwalkar, Stefan Seemayer, Eric Venner, Sunitha K Manjari, Fanny Gatzmann, Aalt D. J. van Dijk, Manfred Roos, Tomislav Šmuc, David T. Jones, Peter Hönigschmid, Ariane Boehm, Florian Auer, Jussi Nokso-Koivisto, Stefano Toppo, Slobodan Vucetic, Denis Krompass, Qingtian Gong, Cajo J. F. ter Braak, Andrew Wong, Barbara Di Camillo, Yiannis A. I. Kourmpetis, Andreas Martin Lisewski, Matko Bošnjak, Bhakti Limaye, Weidong Tian, Yuhong Guo, Xinran Dong, Hai Fang, Yuanpeng Zhou, Stefanie Kaufmann
Publikováno v:
Nature Methods
Nature methods
Nature Methods : techniques for life scientists and chemists 10 (2013)
Nature Methods : techniques for life scientists and chemists, 10, 221-227
Nature Methods, Vol. 10, No 3 (2013) pp. 221-7
Nature methods
Nature Methods : techniques for life scientists and chemists 10 (2013)
Nature Methods : techniques for life scientists and chemists, 10, 221-227
Nature Methods, Vol. 10, No 3 (2013) pp. 221-7
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c19e166af084819ee544097527791f10
http://hdl.handle.net/10449/22010
http://hdl.handle.net/10449/22010
Publikováno v:
BMC Proceedings
Department of Biological Sciences Faculty Publications
Department of Biological Sciences Faculty Publications
Background Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f34596cbcfaca52d748d52bd84a9a78e
https://doi.org/10.1186/1753-6561-6-s7-s5
https://doi.org/10.1186/1753-6561-6-s7-s5
The structural genomics projects have been accumulating an increasing number of protein structures, many of which remain functionally unknown. In parallel effort to experimental methods, computational methods are expected to make a significant contri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f07132452dcd523519654a01a332627c
https://europepmc.org/articles/PMC3375349/
https://europepmc.org/articles/PMC3375349/
Publikováno v:
Department of Biological Sciences Faculty Publications
BMC Bioinformatics, Vol 12, Iss 1, p 373 (2011)
BMC Bioinformatics
BMC Bioinformatics, Vol 12, Iss 1, p 373 (2011)
BMC Bioinformatics
Background Genomics and proteomics experiments produce a large amount of data that are awaiting functional elucidation. An important step in analyzing such data is to identify functional units, which consist of proteins that play coherent roles to ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e90073596610b7e3445e63f0b12eb730
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1019&context=bioscipubs
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1019&context=bioscipubs
Autor:
Meghana Chitale, Daisuke Kihara
Publikováno v:
Protein Function Prediction for Omics Era ISBN: 9789400708808
After reviewing the underlying framework required for computational function prediction in the previous chapter, we discuss two advanced sequence-based function prediction methods developed in our group, namely the Protein Function Prediction (PFP) m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::206525bb1ccfbb8b8716f8274a8020db
https://doi.org/10.1007/978-94-007-0881-5_2
https://doi.org/10.1007/978-94-007-0881-5_2