C. McLean

发表

Creating a universal SNP and small indel variant caller with deep neural networks

Daniel E. Newburger, Nam D. Nguyen, M. DePristo, 2016, bioRxiv.

Human-specific loss of regulatory DNA and the evolution of human-specific traits

Cory Y. McLean, Alex A. Pollen, G. Bejerano, 2011, Nature.

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

David R. Kelley, Maxwell L. Bileschi, Yakir A Reshef, 2018, Genome research.

A deep learning approach to pattern recognition for short DNA sequences

Clara Fannjiang, George E. Dahl, Ryan Poplin, 2018, bioRxiv.

GREAT improves functional interpretation of cis-regulatory regions

Cory Y. McLean, G. Bejerano, M. Hiller, 2010, Nature Biotechnology.

Reducing Pervasive False-Positive Identical-by-Descent Segments Detected by Large-Scale Pedigree Analysis

N. Eriksson, C. McLean, E. Durand, 2013, Molecular biology and evolution.

Mutational Analysis Reveals the Origin and Therapy-Driven Evolution of Recurrent Glioma

Steven J. M. Jones, Richard A. Moore, Jun S. Song, 2014, Science.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

Jenny Chen, G. Bejerano, A. Wenger, 2013, Genome research.

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Waleed Ammar, Jean-Philippe Vert, Quentin Berthet, 2021, bioRxiv.

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

David R. Kelley, Maxwell L. Bileschi, Yakir A Reshef, 2017, bioRxiv.

Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology

D. Sculley, Zachary R. McCaw, Farhad Hormozdiari, 2020, American journal of human genetics.

Dispensability of mammalian DNA.

G. Bejerano, C. McLean, 2008, Genome research.

Longitudinal fundus imaging and its genome-wide association analysis provide evidence for a human retinal aging clock

Boris Babenko, D. Bryant, P. Kapahi, 2022, bioRxiv.

DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer

Cory Y. McLean, Waleed Ammar, Jean-Philippe Vert, 2022, Nature Biotechnology.

An Empirical Study of ML-based Phenotyping and Denoising for Improved Genomic Discovery

F. Hormozdiari, C. McLean, Bo Yuan, 2022, bioRxiv.

Quantifying prion disease penetrance using large population control cohorts

Patrick F. Sullivan, Karen L. Mohlke, M. Arfan Ikram, 2016, Science Translational Medicine.

Knowledge distillation for fast and accurate DNA sequence correction

W. Rowell, Andrew Carroll, A. Wenger, 2022, ArXiv.

A universal SNP and small-indel variant caller using deep neural networks

Thomas Colthurst, Nam Nguyen, David Alexander, 2018, Nature Biotechnology.

DeepNull: Modeling non-linear covariate effects improves phenotype prediction and association power

B. Alipanahi, F. Hormozdiari, N. Furlotte, 2021, bioRxiv.

A population-specific reference panel for improved genotype imputation in African Americans

Jared O'Connell, A. Auton, K. Bryc, 2021, Communications Biology.

DeepNull models non-linear covariate effects to improve phenotypic prediction and association power

B. Alipanahi, F. Hormozdiari, N. Furlotte, 2022, Nature communications.

Underspecification Presents Challenges for Credibility in Modern Machine Learning pdf

Alexander D'Amour, Andrea Montanari, Xiaohua Zhai, 2020, J. Mach. Learn. Res..

Reproducible integration of multiple sequencing datasets to form high-confidence SNP, indel, and reference calls for five human genome reference materials

Chunlin Xiao, Marc Salit, Francisco M. De La Vega, 2018, bioRxiv.

An open resource for accurately benchmarking small variant and reference calls

Chunlin Xiao, Marc Salit, Justin M Zook, 2019, Nature Biotechnology.

DeepTrio: Variant Calling in Families Using Deep Learning

Andrew Carroll, Pi-Chuan Chang, C. McLean, 2021, bioRxiv.

Accurate, scalable cohort variant calls using DeepVariant and GLnexus

Taedong Yun, Cory Y. McLean, Pi-Chuan Chang, 2020, bioRxiv.

Improving Phenotypic Measurements in High-Content Imaging Screens

Marc Berndl, D. Mike Ando, Cory Y. McLean, 2017, bioRxiv.

Diagnosis of Parkinson's disease on the basis of clinical and genetic classification: a population-based modelling study

Margaret Sutherland, John P A Ioannidis, Daniel Weintraub, 2015, The Lancet Neurology.

GREAT , a functional enrichment approach and tool for interpretation of genome-wide cis-regulatory datasets

G. Bejerano, M. Hiller, A. Wenger, 2010 .

SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression pdf

Alexander D'Amour, Steve Yadlowsky, Taedong Yun, 2021, NeurIPS.

Genomewide Association Studies of LRRK2 Modifiers of Parkinson's Disease

James E. Tomkins, B. Alipanahi, J. Trojanowski, 2021, Annals of neurology.

Genome-wide association studies of LRRK2 modifiers of Parkinson's disease

James E. Tomkins, B. Alipanahi, J. Trojanowski, 2020, medRxiv.

A Penile Spine/Vibrissa Enhancer Sequence Is Missing in Modern and Extinct Humans but Is Retained in Multiple Primates with Penile Spines and Sensory Vibrissae

G. Bejerano, C. McLean, P. Reno, 2013, PLoS ONE.

Machine learning guided aptamer refinement and discovery

George E. Dahl, Zan Armstrong, Stephan Hoyer, 2021, Nature Communications.

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models

Cory Y. McLean, F. Hormozdiari, C. McLean, 2023, Nature Genetics.

Epidemic modeling techniques for smallpox

Cory Y. McLean, C. McLean, 2004 .

Accurate human genome analysis with Element Avidity sequencing

S. Kruglyak, Andrew Carroll, B. Lajoie, 2023, bioRxiv.

Multimodal LLMs for health grounded in individual-specific data

Cory Y. McLean, F. Hormozdiari, Greg Corrado, 2023, ML4MHD.

Predicting cardiovascular disease risk using photoplethysmography and deep learning

G. Corrado, Yun Liu, G. Danaei, 2023, PLOS global public health.