
Marylyn D. Ritchie
Articles
-
Nov 28, 2024 |
biorxiv.org | Rachit Kumar |Joseph Romano |Marylyn D. Ritchie
AbstractAccurately determining the binding affinity of a ligand with a protein is important for drug design, development, and screening. With the advent of accessible protein structure prediction methods such as AlphaFold, several approaches have been developed that make use of information determined from the 3D structure for a variety of downstream tasks.
-
Nov 25, 2024 |
mdpi.com | Anni Moore |Marylyn D. Ritchie
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
-
Mar 22, 2024 |
nature.com | Junhao Wen |Bingxin Zhao |Guray Erus |Elizabeth Mamourian |Gyujoon Hwang |Jingxuan Bao | +5 more
AbstractThe complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10−8).
-
Oct 16, 2023 |
nature.com | Tanmoy Roychowdhury |Derek Klarin |Michael Levin |Joshua M. Spin |Colwyn A. Headley |Noah Tsao | +44 more
AbstractAbdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors.
-
May 5, 2023 |
nature.com | Dominic B. Dwyer |Alessandro Pigoni |Junhao Wen |Gyujoon Hwang |Guray Erus |René S. Kahn | +11 more
AbstractUsing machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups—a ‘lower brain volume’ subgroup (SG1) and an ‘higher striatal volume’ subgroup (SG2) with otherwise normal brain structure.
Try JournoFinder For Free
Search and contact over 1M+ journalist profiles, browse 100M+ articles, and unlock powerful PR tools.
Start Your 7-Day Free Trial →