How we roll

Publications

Selected PublicationsAll Publications
Nature Biotechnology
Oct
3
//
2022

Single-Sequence Protein Structure Prediction Using a Language Model and Deep Learning

Ratul Chowdhury, Nazim Bouatta, Surojit Biswas, Christina Floristean, Anant Kharkar, Koushik Roy, Charlotte Rochereau, Gustaf Ahdritz, Joanna Zhang, George M. Church, Peter K. Sorger, Mohammed AlQuraishi
Yes
bioRxiv
May
24
//
2022

High-throughput deep learning variant effect prediction with Sequence UNET

Alistair S. Dunham, Pedro Beltrao, Mohammed AlQuraishi
No
Current Opinion in Chemical Biology
Dec
1
//
2021

Machine Learning in Protein Structure Prediction

Mohammed AlQuraishi
No
Nature Methods
Oct
4
//
2021

Differentiable Biology: Using Deep Learning for Biophysics-based and Data-Driven Modeling of Molecular Mechanisms

Mohammed AlQuraishi, Peter K Sorger
Yes
bioRxiv
Sep
4
//
2021

Protein Structure Prediction Using a Maximum Likelihood Formulation of a Recurrent Geometric Network

Guowei Qi, Mallory R Tollefson, Rose A Gogal, Richard J.H. Smith, Mohammed AlQuraishi, Michael J Schnieders
Nature
Aug
23
//
2021

Protein Structure Prediction Revolutionized

Mohammed AlQuraishi
No
Genome Medicine
Aug
6
//
2021

Recombination and Lineage-specific Mutations Linked to the Emergence of SARS-CoV-2

Juan Ángel Patiño-Galindo, Ioan Filip, Ratul Chowdhury, Costas D. Maranas, Peter K. Sorger, Mohammed AlQuraishi, Raul Rabadan
No
Acta Crystallographica D
Jul
29
//
2021

Protein Structure Prediction by AlphaFold2: Are Attention and Symmetries All You Need?

Nazim Bouatta, Peter Sorger, Mohammed AlQuraishi
Nature
Jan
15
//
2020

A Watershed Moment for Protein Structure Prediction

Mohammed AlQuraishi
No
Nature Methods
Jan
6
//
2020

Biophysical Prediction of Protein–Peptide Interactions and Signaling Networks Using Machine Learning

Joseph M Cunningham, Grigoriy Koytiger, Peter K Sorger, Mohammed AlQuraishi
Yes
Bioinformatics
Nov
15
//
2019

AlphaFold at CASP13

Mohammed AlQuraishi
No
arXiv
Nov
9
//
2019

Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

Iddo Drori, Darshan Thaker, Arjun Srivatsa, Daniel Jeong, Yueqi Wang, Linyong Nan, Fan Wu, Dimitri Leggas, Jinhao Lei, Weiyi Lu, Weilong Fu, Yuan Gao, Sashank Karri, Anand Kannan, Antonio Moretti, Mohammed AlQuraishi, Chen Keasar, Itsik Pe'er
No
Nature Methods
Oct
21
//
2019

Unified Rational Protein Engineering with Sequence-Based Deep Representation Learning

Ethan C Alley, Grigory Khimulya, Surojit Biswas, Mohammed AlQuraishi, George M Church
Yes
BMC Bioinformatics
Jun
11
//
2019

ProteinNet: A Standardized Data Set for Machine Learning of Protein Structure

Mohammed AlQuraishi
No
Cell Systems
Apr
24
//
2019

End-to-End Differentiable Learning of Protein Structure

Mohammed AlQuraishi
Yes
Journal of Computational Chemistry
Jan
7
//
2019

pNeRF: Parallelized Conversion from Internal to Cartesian Coordinates

Mohammed AlQuraishi
No
Science Translational Medicine
May
18
//
2016

Reproducibility Will Only Come with Data Liberation

Mohammed AlQuraishi, Peter K Sorger
No
BMC Bioinformatics
Nov
19
//
2015

An Affinity-Structure Database of Helix-Turn-Helix:DNA Complexes with a Universal Coordinate System

Mohammed AlQuraishi, Shengdong Tang, Xide Xia
No
Nature Genetics
Nov
2
//
2014

A Multiscale Statistical Mechanical Framework Integrates Biophysical and Genomic Data to Assemble Cancer Networks

Mohammed AlQuraishi, Grigoriy Koytiger, Anne Jenney, Gavin MacBeath, Peter K Sorger

Yes
Proteins
Oct
8
//
2012

Three Enhancements to The Inference of Statistical Protein‐DNA Potentials

Mohammed AlQuraishi, Harley H McAdams
No
PNAS
Sep
6
//
2011

Direct Inference of Protein–DNA Interactions Using Compressed Sensing Methods

Mohammed AlQuraishi, Harley H McAdams
Yes