Abbas Alameer

Assistant Professor of Bioinformatics at Kuwait University

Research Expertise

Bioinformatics

Computational Mathematics

Computational Theory and Mathematics

Computer Science Applications

Molecular Biology

Biochemistry

Statistics and Probability

Infectious Diseases

Pharmacology (medical)

Pharmacology

Genetics

About

Abbas Alameer is an Assistant Professor of Bioinformatics at Kuwait University. He received his PhD in Bioinformatics and Molecular Modelling from the University of Leicester in 2014 and his MRes in Bioinformatics and Computational Biology from the University of Leeds in 2006. He has over 10 years of experience in bioinformatics related research and teaching. His research focuses on the computational analysis and modelling of biological molecules, and the development of novel algorithms and Bioinformatics tools. He has published several articles in leading journals in the field and has presented his work at international conferences.

Publications

geoCancerPrognosticDatasetsRetriever: a bioinformatics tool to easily identify cancer prognostic datasets on Gene Expression Omnibus (GEO)

Bioinformatics / Dec 22, 2021

Alameer, A., & Chicco, D. (2021). geoCancerPrognosticDatasetsRetriever: a bioinformatics tool to easily identify cancer prognostic datasets on Gene Expression Omnibus (GEO). Bioinformatics, 38(6), 1761–1763. https://doi.org/10.1093/bioinformatics/btab852

Whole-Genome and Targeted-Amplicon Sequencing of Fluconazole-Susceptible and -Resistant Candida parapsilosis Isolates from Kuwait Reveals a Previously Undescribed N1132D Polymorphism in CDR1

Antimicrobial Agents and Chemotherapy / Jan 20, 2021

Asadzadeh, M., Dashti, M., Ahmad, S., Alfouzan, W., & Alameer, A. (2021). Whole-Genome and Targeted-Amplicon Sequencing of Fluconazole-Susceptible and -Resistant Candida parapsilosis Isolates from Kuwait Reveals a Previously Undescribed N1132D Polymorphism in CDR1. Antimicrobial Agents and Chemotherapy, 65(2). https://doi.org/10.1128/aac.01633-20

Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning

BioData Mining / Nov 03, 2022

Chicco, D., Alameer, A., Rahmati, S., & Jurman, G. (2022). Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning. BioData Mining, 15(1). https://doi.org/10.1186/s13040-022-00312-y

Education

University of Leicester

PhD in Bioinformatics and Molecular Modelling, Department of Molecular and Cell Biology / January, 2014

Leicester

University of Leeds

MRes in Bioinformatics and Computational Biology / December, 2006

Leeds

Experience

Kuwait University

Assistant Professor of Bioinformatics / February, 2014 — Present

Links & Social Media

Research Web Site

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