Zobrazeno 1 - 10
of 149
pro vyhledávání: '"Brendan J. Frey"'
Autor:
Oren Z Kraus, Ben T Grys, Jimmy Ba, Yolanda Chong, Brendan J Frey, Charles Boone, Brenda J Andrews
Publikováno v:
Molecular Systems Biology, Vol 13, Iss 4, Pp n/a-n/a (2017)
Abstract Existing computational pipelines for quantitative analysis of high‐content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training,
Externí odkaz:
https://doaj.org/article/7d17f04c8f62472f87fec588070afc4e
MotivationHi-C data has enabled the genome-wide study of chromatin folding and architecture, and has led to important discoveries in the structure and function of chromatin conformation. Here, high resolution data plays a particularly important role
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a882643aa99e0f989617a40ff4a748dc
Autor:
Piya Lahiry, Leo J Lee, Brendan J Frey, C Anthony Rupar, Victoria M Siu, Benjamin J Blencowe, Robert A Hegele
Publikováno v:
PLoS ONE, Vol 6, Iss 9, p e25400 (2011)
Transcriptome profiling of patterns of RNA expression is a powerful approach to identify networks of genes that play a role in disease. To date, most mRNA profiling of tissues has been accomplished using microarrays, but next-generation sequencing ca
Externí odkaz:
https://doaj.org/article/0e1622b55c4142d5abbb0db4e4b833b3
Autor:
Mark Sun, Frank W. Schmitges, Jiexin Gao, Brendan J. Frey, Marta Verby, Amit G. Deshwar, Solomon Grant, Ken Kron, Phil Fradkin, James J. Dowling, Johan E. S. Fransson, Matthew O’Hara, Carl Spickett, Boyko Kakaradov, Daniele Merico, Matthew Cahill, Shreshth Gandhi, Zvi Shalev, Erno Wienholds
Publikováno v:
npj Genomic Medicine, Vol 5, Iss 1, Pp 1-7 (2020)
NPJ Genomic Medicine
NPJ Genomic Medicine
Wilson disease is a recessive genetic disorder caused by pathogenic loss-of-function variants in the ATP7B gene. It is characterized by disrupted copper homeostasis resulting in liver disease and/or neurological abnormalities. The variant NM_000053.3
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31aef81e415ed0b18a0b2bffd0453778
Publikováno v:
Bioinformatics
Motivation : High-content screening (HCS) technologies have enabled large scale imaging experiments for studying cell biology and for drug screening. These systems produce hundreds of thousands of microscopy images per day and their utility depends o
Publikováno v:
Proceedings of the IEEE. 104:176-197
In this paper, we provide an introduction to machine learning tasks that address important problems in genomic medicine. One of the goals of genomic medicine is to determine how variations in the DNA of individuals can affect the risk of different di
Autor:
Bhooma Thiruvahindrapuram, Stephen W. Scherer, Brendan J. Frey, Daniele Merico, Christian R. Marshall, Thomas Nalpathamkalam, Gregory Costain, Babak Alipanahi, Eva W.C. Chow, Mehdi Zarrei, Nancy J. Butcher, Danielle M. Andrade, Lucas Ogura, Matthew J. Gazzellone, Anne S. Bassett
Publikováno v:
G3: Genes|Genomes|Genetics
Chromosome 22q11.2 microdeletions impart a high but incomplete risk for schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 haploinsufficiency. In a proof-of-principle study to assess the power of this model, we used high-quality,
MotivationDetermining RNA binding protein(RBP) binding specificity is crucial for understanding many cellular processes and genetic disorders. RBP binding is known to be affected by both the sequence and structure of RNAs. Deep learning can be used t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ae296e78bad234e342eea8724809307
Genetic variation has long been known to alter transcription factor binding sites, resulting in sometimes major phenotypic consequences. While the performance for current binding site predictors is well characterised, little is known on how these mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3815bc2a305c36e4b957f100d3fe6c1
https://doi.org/10.1101/253427
https://doi.org/10.1101/253427
Publikováno v:
Bioinformatics
Motivation Alternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends on the strength of neighboring sites. Here, we present a new model named the competitive splice site model (COSS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8faef4f108c32dca10721d3f44e5e56e
https://doi.org/10.1101/255257
https://doi.org/10.1101/255257