Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sarah ElShal"'
Autor:
Raymond Kassekert, Neal Grabowski, Denny Lorenz, Claudia Schaffer, Dieter Kempf, Promit Roy, Oeystein Kjoersvik, Griselda Saldana, Sarah ElShal
Publikováno v:
Drug Safety. 45:439-448
TransCelerate reports on the results of 2019, 2020, and 2021 member company (MC) surveys on the use of intelligent automation in pharmacovigilance processes. MCs increased the number and extent of implementation of intelligent automation solutions th
Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information
Publikováno v:
Bioinformatics
Motivation Most gene prioritization methods model each disease or phenotype individually, but this fails to capture patterns common to several diseases or phenotypes. To overcome this limitation, we formulate the gene prioritization task as the facto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2913744225abd846525b57f7180e09aa
https://lirias.kuleuven.be/handle/123456789/645586
https://lirias.kuleuven.be/handle/123456789/645586
Publikováno v:
BIBM
The massive growth of biomedical text makes it very challenging for researchers to review all relevant work and generate all possible hypotheses in a reasonable amount of time. Many text mining methods have been developed to simplify this process and
Autor:
Yves Moreau, Sarah ElShal, Daniel Alcaide, Léon-Charles Tranchevent, Jan Aerts, Amin Ardeshirdavani, Didier Auboeuf
Publikováno v:
Nucleic Acids Research
Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f60f8e1ecb16cc4a22b0c18dbf55aae3
https://lirias.kuleuven.be/handle/123456789/539739
https://lirias.kuleuven.be/handle/123456789/539739
Publikováno v:
Bioinformatics and Biomedical Engineering ISBN: 9783319317434
IWBBIO
IWBBIO
© Springer International Publishing Switzerland 2016. Text mining is popular in biomedical applications because it allows retrieving highly relevant information. Particularly for us, it is quite practical in linking diseases to the genes involved in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2707ed6f1be6e4fb010594c03bfed90
https://doi.org/10.1007/978-3-319-31744-1_66
https://doi.org/10.1007/978-3-319-31744-1_66
Autor:
Yuxiang Jiang, Tal Ronnen Oron, Wyatt T. Clark, Asma R. Bankapur, Daniel D’Andrea, Rosalba Lepore, Christopher S. Funk, Indika Kahanda, Karin M. Verspoor, Asa Ben-Hur, Da Chen Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed M. E. Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T. Jones, Samuel Chapman, Dukka BKC, Ishita K. Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E. Foulger, Reija Hieta, Duncan Legge, Ruth C. Lovering, Michele Magrane, Anna N. Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L. Dawson, David Lee, Jonathan G. Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E. Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E. Sedeño-Cortés, Paul Pavlidis, Shou Feng, Juan M. Cejuela, Tatyana Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo Ferrari, Manuel Giollo, Damiano Piovesan, Silvio C.E. Tosatto, Angela del Pozo, José M. Fernández, Paolo Maietta, Alfonso Valencia, Michael L. Tress, Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W. Bargsten, Aalt D. J. van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C. Almeida-e-Silva, Ricardo Z. N. Vencio, Malvika Sharan, Jörg Vogel, Lakesh Kansakar, Shanshan Zhang, Slobodan Vucetic, Zheng Wang, Michael J. E. Sternberg, Mark N. Wass, Rachael P. Huntley, Maria J. Martin, Claire O’Donovan, Peter N. Robinson, Yves Moreau, Anna Tramontano, Patricia C. Babbitt, Steven E. Brenner, Michal Linial, Christine A. Orengo, Burkhard Rost, Casey S. Greene, Sean D. Mooney, Iddo Friedberg, Predrag Radivojac
Publikováno v:
Repositorio Institucional de la Consejería de Sanidad de la Comunidad de Madrid
Consejería de Sanidad de la Comunidad de Madrid
Genome Biology
Genome Biology, 17 (1)
17:184
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Genome Biology, vol. 17, no. 1, pp. 184
Recercat. Dipósit de la Recerca de Catalunya
instname
Repisalud
Instituto de Salud Carlos III (ISCIII)
Genome Biology 17 (2016) 1
Genome Biology, 17(1)
Consejería de Sanidad de la Comunidad de Madrid
Genome Biology
Genome Biology, 17 (1)
17:184
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Genome Biology, vol. 17, no. 1, pp. 184
Recercat. Dipósit de la Recerca de Catalunya
instname
Repisalud
Instituto de Salud Carlos III (ISCIII)
Genome Biology 17 (2016) 1
Genome Biology, 17(1)
BACKGROUND: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec8a6a0d9eaae66e982189e622e9e4d4
http://hdl.handle.net/10449/37272
http://hdl.handle.net/10449/37272
Publikováno v:
BIBM
In biology there is often the need to discover the most promising genes, among a large list of candidate genes, to further investigate. While a single data source might not be effective enough, integrating several complementary genomic data sources l
Autor:
Amin Ardeshirdavani, Léon-Charles Tranchevent, Sarah ElShal, Jesse Davis, Yves Moreau, Alejandro Sifrim
Publikováno v:
Nucleic Acids Research
Disease-gene identification is a challenging process that has multiple applications within functional genomics and personalized medicine. Typically, this process involves both finding genes known to be associated with the disease (through literature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fa2dbdbf7d7217ccd2f479b7cdfe6d1
https://lirias.kuleuven.be/handle/123456789/510968
https://lirias.kuleuven.be/handle/123456789/510968
Publikováno v:
EMBnet.journal. 18:108
Motivation and Objectives Because of the amount of electronic literature now available, it is challenging for biologists to search biomedical corpuses for any kind of desired information beyond simple text retrieval. Several tools have been developed