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プロフィール詳細

プロジェクトを作成

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Dr. Hamid Mustafa P.に依頼

Pakistan

PhD Genomics Expert | Livestock Breeding, SNP Data Analysis, GWAS & Bioinformatics Consulting

プロフィール概要

I am a PhD-level Animal Genomics and Bioinformatics expert with over 15 years of experience in livestock breeding, quantitative genetics, and computational biology. Currently serving as Assistant Professor at the University of Veterinary and Animal Sciences (UVAS), Pakistan, I specialize in integrating genomic data with advanced statistical and machine learning approaches to solve complex biological and production challenges in livestock.

My expertise includes genome-wide association studies (GWAS), SNP data analysis, runs of homozygosity (ROH), selection signature analysis, genomic prediction (GEBV), and multi-omics integration (transcriptomics, methylation, and functional genomics). I have extensive experience working with high-density SNP arrays (e.g., Illumina, Axiom), and tools such as PLINK, R, Python, ASReml, and Beagle for large-scale genomic data analysis.

I have successfully led and contributed to multiple high-value national and international research projects (>$1M cumulative), including work on disease resistance (bovine tuberculosis), genetic improvement of dairy cattle and buffalo, and the establishment of genomic selection programs. My research collaborations include partnerships with USDA (USA), international universities, and national livestock research institutes.

I offer consulting services in:
• Genomic data analysis (GWAS, ROH, LD, PCA, FST, CNV)
• Livestock breeding program design and genetic evaluation
• Machine learning applications in animal breeding
• Bioinformatics pipelines for genomics and transcriptomics
• Research proposal development and scientific writing (Q1 journals)

I am committed to delivering scientifically rigorous, publication-quality results with clear interpretation and actionable insights for research, industry, and policy applications.

専門分野

サービス

Writing
Research
Consulting
Data & AI

Writing Clinical Trial Documentation, Medical Writing, Non-Medical Regulatory Writing, Creative Writing, Audio Transcription

Research User Research, Meta-Research, Feasibility Study, Technology Scouting, Gap Analysis, Gray Literature Search, Scientific and Technical Research, Systematic Literature Review

Consulting Operations Consulting, Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Algorithm Design-ML, Data Visualization, Big Data Analytics, Data Mining

職務経験

Assistant Professor

University of Veterinary and Animal Sciences

- 現在

学歴

PhD

United States Department of Agriculture

1月 2026 - 現在

認定資格

Data Analysis

USDA

1月 2026 - 現在

出版物

PREPRINT

Hamid Mustafa, Atiq Ahmad, Waqas Ahmad Khan, Asif Rafiq, Ishtiaque Ahmad, Haiba Kaul, Seema Baloch, Abdul Manan, Waqas Akram (2026). Pattern of Runs of Homozygosity and Selection Signatures in Nili Ravi Buffalo .

Hamid Mustafa, Mohammed Al-Abri, Waqas Akram, Haiba Kaul, Waqas Ahmad Khan, Jong-Joo Kim, Muhammad Bilal Bin Majeed (2026). Selection Signatures at PRLR and Heat Shock Protein Genes Reveal the Genetic Basis of Heat Stress Adaptation in Cattle .

JOURNAL ARTICLE

Genetic Association of Beta-Myosin Heavy-Chain Gene (MYH7) with Cardiac Dysfunction <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> . Genes.

Hamid Mustafa, Memoona Yousaf, Waqas Ahmed Khan, Khurrum Shahzad, Haq Nawaz Khan, Basharat Ali, Misbah Hussain, Fazli Rabbi Awan, Farah Nadia Sheikh (2022). Genetic Association of Beta-Myosin Heavy-Chain Gene (MYH7) with Cardiac Dysfunction . Genes.

WORKING PAPER

Selection Signatures at PRLR and Heat Shock Protein Genes Reveal the Genetic Basis of Heat Stress Adaptation in Cattle .

Pattern of Runs of Homozygosity and Selection Signatures in Nili Ravi Buffalo .

level-one heading

PhD Genomics Expert | Livestock Breeding, SNP Data Analysis, GWAS & Bioinformatics Consulting

Assistant Professor

University of Veterinary and Animal Sciences

PhD

United States Department of Agriculture

Data Analysis

USDA