Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Žiga Avsec"'
Autor:
Jun Cheng, Thi Yen Duong Nguyen, Kamil J. Cygan, Muhammed Hasan Çelik, William G. Fairbrother, žiga Avsec, Julien Gagneur
Publikováno v:
Genome Biology, Vol 20, Iss 1, Pp 1-15 (2019)
Abstract Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping prediction chall
Externí odkaz:
https://doaj.org/article/00725e339fa84734b0b17a4ab4e0dc83
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 5, p e1008982 (2021)
The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR regulatory sequences shall provide insights into translational control mechanisms and help interpret
Externí odkaz:
https://doaj.org/article/de07f319f31f466bb7988d7fd7f6a845
Autor:
Rita Casadio, Jun Cheng, Ron Unger, Žiga Avsec, Ken Chen, Noa E. Cohen, Julien Gagneur, Chiao-Feng Lin, Robert Y. Wang, William G. Fairbrother, Yuedong Yang, Tamar Holzer, Thi Yen Duong Nguyen, Pier Luigi Martelli, Tzila Fenesh, Liran Carmel, Stephen M. Mount, Valer Gotea, Castrense Savojardo, Muhammed Hasan Çelik, Huiying Zhao, Tatsuhiko Naito
Publikováno v:
Hum Mutat
Precision medicine and sequence-based clinical diagnostics seek to predict disease risk or to identify causative variants from sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f7a4bba14a76c9632487441ac2721f2
https://doi.org/10.1002/humu.23869
https://doi.org/10.1002/humu.23869
Autor:
Roman Kreuzhuber, Nancy Xu, Thorsten Beier, Žiga Avsec, Daniel S Kim, Jun Cheng, Johnny Israeli, Lara Urban, Avanti Shrikumar, Anshul Kundaje, Abhimanyu Banerjee, Oliver Stegle, Julien Gagneur
Publikováno v:
Nature biotechnology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2045b4de801200c5045ac1f8a0b6ce44
http://europepmc.org/articles/PMC6777348
http://europepmc.org/articles/PMC6777348
Autor:
Agnieszka Grabska-Barwinska, Kyle R. Taylor, Žiga Avsec, Pushmeet Kohli, Daniel Visentin, John M. Jumper, David R. Kelley, Joseph R. Ledsam, Vikram Agarwal, Yannis M. Assael
Publikováno v:
Nature Methods
How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49ff44bafa5e6961f7e3193418ee0609
https://doi.org/10.1101/2021.04.07.438649
https://doi.org/10.1101/2021.04.07.438649
Autor:
Amr Alexandari, Avanti Shrikumar, Julia Zeitlinger, Charles McAnany, Žiga Avsec, Melanie Weilert, Anshul Kundaje, Khyati Dalal, Julien Gagneur, Sabrina Krueger, Robin Fropf
Publikováno v:
Nature genetics. 53(3)
The arrangement (syntax) of transcription factor (TF) binding motifs is an important part of the cis-regulatory code, yet remains elusive. We introduce a deep learning model, BPNet, that uses DNA sequence to predict base-resolution chromatin immunopr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e66e595d5c08f7809579c123009ea273
https://pubmed.ncbi.nlm.nih.gov/33686263
https://pubmed.ncbi.nlm.nih.gov/33686263
Publikováno v:
RNA
The stability of mRNA is one of the major determinants of gene expression. Although a wealth of sequence elements regulating mRNA stability has been described, their quantitative contributions to half-life are unknown. Here, we built a quantitative m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9307a126eeb408f0ec4b10f6cada70a
https://doi.org/10.1261/rna.062224.117
https://doi.org/10.1261/rna.062224.117
Autor:
Avanti Shrikumar, Julia Zeitlinger, Charles McAnany, Khyati Dalal, Melanie Weilert, Julien Gagneur, Žiga Avsec, Anshul Kundaje, Sabrina Krueger, Robin Fropf, Amr Alexandari
SummaryThe arrangement of transcription factor (TF) binding motifs (syntax) is an important part of the cis-regulatory code, yet remains elusive. We introduce a deep learning model, BPNet, that uses DNA sequence to predict base-resolution ChIP-nexus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::827a19aec6fe26a5ce1beaada1146c7d
https://doi.org/10.1101/737981
https://doi.org/10.1101/737981
Publikováno v:
Hum Mutat
Pathogenic genetic variants are often primarily affecting splicing. However, it remains difficult to quantitatively predict whether and how genetic variants affect splicing. In 2018, the fifth edition of the Critical Assessment of Genome Interpretati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c646917e6aa610f50c8722421e88cff5
https://pubmed.ncbi.nlm.nih.gov/31070280
https://pubmed.ncbi.nlm.nih.gov/31070280
Autor:
Jun Cheng, Julien Gagneur, Nguyen Tyd, Žiga Avsec, Muhammed Hasan Çelik, Kamil J. Cygan, William G. Fairbrother
Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI 2018 exon skipping prediction challenge.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a6ab7f0c7ee2bd6a863be3a2bc7db98