Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Alex Hawkins"'
Autor:
Alex Hawkins-Hooker, Giovanni Visonà, Tanmayee Narendra, Mateo Rojas-Carulla, Bernhard Schölkopf, Gabriele Schweikert
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Abstract Epigenetic modifications are dynamic mechanisms involved in the regulation of gene expression. Unlike the DNA sequence, epigenetic patterns vary not only between individuals, but also between different cell types within an individual. Enviro
Externí odkaz:
https://doaj.org/article/8d8c4ed4fb5f4b7e99cc02481437355d
Autor:
Jacob Schreiber, Carles Boix, Jin wook Lee, Hongyang Li, Yuanfang Guan, Chun-Chieh Chang, Jen-Chien Chang, Alex Hawkins-Hooker, Bernhard Schölkopf, Gabriele Schweikert, Mateo Rojas Carulla, Arif Canakoglu, Francesco Guzzo, Luca Nanni, Marco Masseroli, Mark James Carman, Pietro Pinoli, Chenyang Hong, Kevin Y. Yip, Jeffrey P. Spence, Sanjit Singh Batra, Yun S. Song, Shaun Mahony, Zheng Zhang, Wuwei Tan, Yang Shen, Yuanfei Sun, Minyi Shi, Jessika Adrian, Richard Sandstrom, Nina Farrell, Jessica Halow, Kristen Lee, Lixia Jiang, Xinqiong Yang, Charles Epstein, J. Seth Strattan, Bradley Bernstein, Michael Snyder, Manolis Kellis, William Stafford, Anshul Kundaje, ENCODE Imputation Challenge Participants
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-22 (2023)
Abstract A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measu
Externí odkaz:
https://doaj.org/article/af322f5b401248609628ec2ad86cadd9
Autor:
Alex Hawkins-Hooker, Florence Depardieu, Sebastien Baur, Guillaume Couairon, Arthur Chen, David Bikard
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 2, p e1008736 (2021)
The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequ
Externí odkaz:
https://doaj.org/article/ccbb1d5f2fab42edb2423c43e84cf1d1
Publikováno v:
Veterinary Surgery. 51:311-319
Autor:
Maty G.P. Looijen, Alex Hawkins, Dagmar Berner, Jennifer Rose Irving, Jonathan Williams, Ricky Farr, Roger K. Smith, Andrew Fiske‐Jackson
Publikováno v:
Equine Veterinary Education. 35
Publikováno v:
Equine Veterinary Journal. 54:312-322
Background Injuries to the oblique (ODSL) or straight (SDSL) distal sesamoidean ligaments are a recognised cause of distal limb lameness in the horse. However, there are only limited publications addressing common diagnostic features and prognosis. O
Autor:
Alex Hawkins-Hooker, Giovanni Visona, Tanmayee Narendra, Mateo Rojas-Carulla, Bernhard Schölkopf, Gabriele Schweikert
Epigenetic modifications are dynamic control mechanisms involved in the regulation of gene expression. Unlike the DNA sequence itself, they vary not only between individuals but also between different cell types of the same individual. Exposure to en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82aea16b3928e2bc85dbe12b013fb25a
https://doi.org/10.1101/2022.02.11.479115
https://doi.org/10.1101/2022.02.11.479115
Autor:
Ron Unger, Jay Shendure, Ayoti Patra, Beth Martin, Henry Kenlay, Zhongxia Yan, Anat Kreimer, Michael A. Beer, Nir Yosef, Dmitry Penzar, Martin Kircher, Max Schubach, Tamar Juven-Gershon, John E. Reid, Alan P. Boyle, Alex Hawkins-Hooker, Aashish N. Adhikari, Orit Adato, Nadav Ahituv, Ivan V. Kulakovskiy, Fumitaka Inoue, Chenling Xiong, Shengcheng Dong, Dustin Shigaki
Publikováno v:
Human mutation, vol 40, iss 9
Hum Mutat
Hum Mutat
The integrative analysis of high-throughput reporter assays, machine learning, and profiles of epigenomic chromatin state in a broad array of cells and tissues has the potential to significantly improve our understanding of noncoding regulatory eleme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::faf4702d3ab08dea7d071fe506df43ac
https://escholarship.org/uc/item/3rg6s3n3
https://escholarship.org/uc/item/3rg6s3n3
With the increasing application of deep learning methods to the modelling of regulatory DNA sequences has come an interest in exploring what types of architecture are best suited to the domain. Networks designed to predict many functional characteris
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cdda028a4a71f46e1dba72bf233a6b6