Summer Sale

Up to 30% off — ends 7 Aug

ONLY00h00m00s

Get 30% Off

Up to 30% off — ends 7 Aug

ONLY00h00m00s

Hao Cheng

Associate Professor

University of California, Davis

United States

This profile is automatically generated from trusted academic sources.

Google Scholar

ORCID

How do I reach out?

Meet Kite AI

Contact this professor

ORCID

Google Scholar

Research Interests

Biostatistics

90%

Animal Science

20%

Genomic

70%

Genome-wide Association

60%

Quantitative Genetics

40%

Genetic

40%

Conservation Genetics

20%

Ask ApplyKite AI

Start chatting

How can you help me contact this professor?

What are this professor's research interests?

How should I write an email to this professor?

Articles10

Genome-wide association studies for egg quality traits in White Leghorn layers using low-pass sequencing and SNP chip data

Article Link

Year:

2022

Genome-wide association study of disease resilience traits from a natural polymicrobial disease challenge model in pigs identifies the importance of the major histocompatibility complex region

Article Link

Year:

2022

Interpretable artificial neural networks incorporating Bayesian alphabet models for genome-wide prediction and association studies

Article Link

Year:

2021

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

Article Link

Year:

2021

Optimizing Sequencing Resources in Genotyped Livestock Populations Using Linear Programming

Article Link

Year:

2021

Single-Trait and Multiple-Trait Genomic Prediction From Multi-Class Bayesian Alphabet Models Using Biological Information

Article Link

Year:

2021

Tests of association based on genomic windows can lead to spurious associations when using genotype panels with heterogeneous SNP densities

Article Link

Year:

2021

The accuracy of genomic predictions for bacterial cold water disease resistance remains higher than the pedigree-based model one generation after model training in a commercial rainbow trout breeding population

Article Link

Year:

2021

A multiple-trait Bayesian variable selection regression method for integrating phenotypic causal networks in genome-wide association studies

Article Link

Year:

2020

Assessing Accuracy of Genomic Predictions for Resistance to Infectious Hematopoietic Necrosis Virus With Progeny Testing of Selection Candidates in a Commercial Rainbow Trout Breeding Population

Article Link

Year:

2020

Collaborators4

Tianjing Zhao

Assistant Professor in theoretical quantitative genetics

University of Nebraska - Lincoln

UNITED STATES

Stephen Kachman

Professor

University of Nebraska - Lincoln

UNITED STATES

Rohan Fernando

Professor Emeritus of Animal Science

Iowa State University

UNITED STATES

Daniel Runcie

Assistant Professor

University of California, Davis

UNITED STATES

How do I reach out?

Meet Kite AI