Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Zohair Shafi"'
Autor:
Ayan Chatterjee, Robin Walters, Zohair Shafi, Omair Shafi Ahmed, Michael Sebek, Deisy Gysi, Rose Yu, Tina Eliassi-Rad, Albert-László Barabási, Giulia Menichetti
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-15 (2023)
State-of-the-art machine learning models in drug discovery fail to reliably predict the binding properties of poorly annotated proteins and small molecules. Here, the authors present AI-Bind, a machine learning pipeline to improve generalizability an
Externí odkaz:
https://doaj.org/article/6269a5ed797a41ff898a72b3ecaaee47
Autor:
Ayan Chatterjee, Robin Walters, Zohair Shafi, Omair Shafi Ahmed, Michael Sebek, Deisy Gysi, Rose Yu, Tina Eliassi-Rad, Albert-László Barabási, Giulia Menichetti
Identifying novel drug-target interactions (DTI) is a critical and rate limiting step in drug discovery. While deep learning models have been proposed to accelerate the identification process, we show that state-of-the-art models fail to generalize t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85a8378f02f25571b01e64a6d371d41f
http://arxiv.org/abs/2112.13168
http://arxiv.org/abs/2112.13168
Autor:
Scott Alfeld, Benjamin A. Miller, Yevgeniy Vorobeychik, Zohair Shafi, Wheeler Ruml, Tina Eliassi-Rad
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Research Track ISBN: 9783030865191
ECML/PKDD (2)
ECML/PKDD (2)
Shortest paths in complex networks play key roles in many applications. Examples include routing packets in a computer network, routing traffic on a transportation network, and inferring semantic distances between concepts on the World Wide Web. An a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cef9fd26180498d5c1e11ee637e8fe57
https://doi.org/10.1007/978-3-030-86520-7_33
https://doi.org/10.1007/978-3-030-86520-7_33
Publikováno v:
AIES
We present RAWLSNET, a system for altering Bayesian Network (BN) models to satisfy the Rawlsian principle of fair equality of opportunity (FEO). RAWLSNET's BN models generate aspirational data distributions: data generated to reflect an ideally fair,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c69054973a16cd170e5c9bc6d72e0a0
Data driven decision making is becoming increasingly an important aspect for successful business execution. More and more organizations are moving towards taking informed decisions based on the data that they are generating. Most of this data are in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f89e2047beb4b1c562443a5cb7c1e18
https://doi.org/10.7287/peerj.preprints.27959v1
https://doi.org/10.7287/peerj.preprints.27959v1