Match tier
Listed
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-05
Y
Yasir Rahmatallah
Associate Professor
Also affiliated: Queen's University Belfast (2013); University of Arkansas Medical Center (2018–2020); University of Arkansas System (2011–2020); Tampere University of Technology (2015)
Biomedical Informatics, College of Medicine
19 h-index
100 pubs
1,714 cited
Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Yasir Rahmatallah's research focuses on the application of computational methods and machine learning to analyze biological data, with a particular emphasis on disease mechanisms and biomarker discovery. His work includes developing machine learning models for the early identification of Parkinson's disease using voice samples, as demonstrated in his 2023 and 2025 publications. Rahmatallah also investigates gene expression patterns in plants, specifically examining how beneficial bacteria influence rice growth and stress responses, as detailed in his 2022 and 2023 studies. His research extends to human health, with publications on inflammatory dysregulation and the comparative effects of antiplatelet medications in patients with chronic kidney disease. Rahmatallah has a significant publication record, with 98 total publications and 1,650 citations, and an h-index of 19. He collaborates with researchers at the University of Arkansas for Medical Sciences, including Mohammed S. Orloff, David W. Ussery, and Horacio Gómez-Acevedo, as well as Ebrahim Jakoet from the University of Arkansas at Little Rock.
Metrics
- h-index: 19
- Publications: 100
- Citations: 1,714
Positions
-
Associate Professor 2024–presentUniversity of Arkansas for Medical Sciences Biomedical Informatics, College of Medicine Institutional directory
-
Assistant Professor 2016–2024University of Arkansas for Medical Sciences Biomedical Informatics ORCID
-
Postdoc Fellow 2011–2016University of Arkansas for Medical Sciences Biomedical Informatics ORCID
-
Postdoc Fellow 2011University of Arkansas at Little Rock Systems Engineering ORCID
Selected Publications
-
Author Correction: A machine learning method to process voice samples for identification of Parkinson’s disease (2026)
-
Abstract 7642: Nicotine dependence partially mediates the association between <i>IP6K3</i> genetic variation and risk of lung squamous cell carcinoma among smokers (2026)
-
ZNF16 is a nucleolar-associated protein that regulates expression of rDNA and cancer-associated genes (2025)
-
SAT-016 Musashi Contributes to the Specification and Maintenance of Distinct Pituitary Cell Lineages. (2025)
-
ZNF16 is a nucleolar-associated protein that regulates expression of the rDNA and cancer-associated genes (2025)
-
A Tracts of Homozygosity Approach Identifies Methylation-Regulated <i>CSMD1</i> Expression Targets in Non–Small Cell Lung Cancers Related to Smoking Behavior (2025)
-
Abstract 1923: A tract of homozygosity analysis reveals methylation-driven <i>CSMD1</i> expression in non-small cell lung cancers (2025)
-
Improving data interpretability with new differential sample variance gene set tests (2025)
-
Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples (2025)
-
Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples (2024)
-
Higher Glycolysis in Circulating Leukocytes in Patients with CKD (2024)
-
Improving data interpretability with new differential sample variance gene set tests (2024)
Grants & Funding
As listed on this researcher's institutional profile.
- Epigenetic regulation of differentially expressed genes in cutaneous T-cell lymphoma VA/CAVHS Co-Investigator
- Partnerships for Biomedical Research in Arkansas NIH Co-Investigator
- Formation of the IDeA National Resource for Proteomics NIH/NIGMS Co-Investigator
- Expand data science training, access to publicly available data, and computational resources within the Arkansas INBRE network NIH/NIGMS Co-Investigator
- Platelet-Leukocyte Axis in Patients with Chronic Kidney Disease NIH/NIGMS Co-Investigator
- Integrating Gene Expression Profiles from Different Platforms into a Robust and Clinically Relevant Prognostic and Predictive Tool for Pediatric Leukemia NIH/NIGMS Principal Investigator
- Center for Translational Pediatric Research NIH/NIGMS Co-Investigator
- Resources for Development and Validation of Radiomic Analyses and Adaptive Therapy NIH/NCI Co-Investigator
- Phone-Collected Speech Corpus for Remote Assessment of Parkinson’s Disease UAMS College of Medicine Principal Investigator
- Comparison of different health care delivery methods in a rural underserved population of People with Parkinson's Disease UAMS Translational Research Institute Co-Investigator
- Machine Learning Approaches for Remote Pathological Speech Assessment for Parkinson's Disease NSF Arkansas EPSCoR Select
Collaboration Network
Top Collaborators
Galina Glazko
University of Arkansas for Medical Sciences
26 shared publications
In database
- Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets
- Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline
- RNA-seq reveals differentially expressed genes in rice (Oryza sativa) roots during interactions with plant-growth promoting bacteria, Azospirillum brasilense
- GSAR: Bioconductor package for Gene Set analysis in R
- 16S rRNA Gene-Based Metagenomic Analysis of Ozark Cave Bacteria
Showing 5 of 26 shared publications
Seshadri Mohan
University of Arkansas at Little Rock
8 shared publications
In database
- Peak-To-Average Power Ratio Reduction in OFDM Systems: A Survey And Taxonomy
- Mutual coupling reduction of dual-band printed monopoles using MNG metamaterial
- Bit Error Rate Performance of Linear Companding Transforms for PAPR Reduction in OFDM Systems
- Bit-Error-Rate Performance of Companding Transforms for OFDM
- On the performance of linear and nonlinear companding transforms in OFDM systems
Showing 5 of 8 shared publications
Frank Emmert‐Streib
Tampere University (FI)
7 shared publications
- Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets
- Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline
- GSAR: Bioconductor package for Gene Set analysis in R
- Gene set analysis for self-contained tests: complex null and specific alternative hypotheses
- Comparative evaluation of gene set analysis approaches for RNA-Seq data
Showing 5 of 7 shared publications
Boris Zybailov
University of Arkansas for Medical Sciences
6 shared publications
In database
- GSAR: Bioconductor package for Gene Set analysis in R
- Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats
- Protein-protein interaction analysis for functional characterization of helicases
- Extracting the Strongest Signals from Omics Data: Differentially Expressed Pathways and Beyond
- Milk Formula Diet Alters Bacterial and Host Protein Profile in Comparison to Human Milk Diet in Neonatal Piglet Model
Showing 5 of 6 shared publications
Arijit Mukherjee
University of Central Arkansas (US)
5 shared publications
- RNA-seq reveals differentially expressed genes in rice (Oryza sativa) roots during interactions with plant-growth promoting bacteria, Azospirillum brasilense
- Common gene expression patterns are observed in rice roots during associations with plant growth-promoting bacteria, Herbaspirillum seropedicae and Azospirillum brasilense
- Azospirillum brasilense improves rice growth under salt stress by regulating the expression of key genes involved in salt stress response, abscisic acid signaling, and nutrient transport, among others
- The plant growth-promoting bacteria, Azospirillum brasilense, induce a diverse array of genes in rice shoots and promote their growth
- Investigating the transcriptomic responses in rice roots during interactions with plant growth‐promoting bacteria, <i>Burkholderia unamae</i>
Anu Iyer
Georgia Institute of Technology (US)
5 shared publications
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
- Author Correction: A machine learning method to process voice samples for identification of Parkinson’s disease
Tuhin Virmani
University of Arkansas for Medical Sciences
5 shared publications
In database
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
- Author Correction: A machine learning method to process voice samples for identification of Parkinson’s disease
Nidhal Bouaynaya
University of Arkansas at Little Rock (US)
4 shared publications
- Bit Error Rate Performance of Linear Companding Transforms for PAPR Reduction in OFDM Systems
- Bit-Error-Rate Performance of Companding Transforms for OFDM
- On the performance of linear and nonlinear companding transforms in OFDM systems
- ARMA companding scheme with improved symbol error rate for PAPR reduction in OFDM systems
Stephanie D. Byrum
University of Arkansas for Medical Sciences
4 shared publications
In database
- Metaproteomics reveals potential mechanisms by which dietary resistant starch supplementation attenuates chronic kidney disease progression in rats
- RNA-Seq Analysis of Spinal Cord Tissues from hPFN1G118V Transgenic Mouse Model of ALS at Pre-symptomatic and End-Stages of Disease
- Milk Formula Diet Alters Bacterial and Host Protein Profile in Comparison to Human Milk Diet in Neonatal Piglet Model
- SAT-016 Musashi Contributes to the Specification and Maintenance of Distinct Pituitary Cell Lineages.
Aaron S. Kemp
University of Arkansas for Medical Sciences
4 shared publications
In database
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
Lakshmi Pillai
University of Arkansas for Medical Sciences
4 shared publications
In database
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
Fred Prior
University of Arkansas for Medical Sciences
4 shared publications
In database
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
Linda Larson‐Prior
University of Arkansas for Medical Sciences
4 shared publications
In database
- A machine learning method to process voice samples for identification of Parkinson’s disease
- Pre-trained convolutional neural networks identify Parkinson’s disease from spectrogram images of voice samples
- A Machine Learning Method to Process Voice Samples for Identification of Parkinson’s Disease
- Pre-trained Convolutional Neural Networks Identify Parkinson’s Disease from Spectrogram Images of Voice Samples
Haider R. Khaleel
University of Arkansas at Little Rock (US)
3 shared publications
- Mutual coupling reduction of dual-band printed monopoles using MNG metamaterial
- An investigation on the effect of bending of Split Ring Resonators
- An investigation on the effect of bending on UC-PBG structures
Hussain M. Al‐Rizzo
University of Arkansas at Little Rock
3 shared publications
In database
- Mutual coupling reduction of dual-band printed monopoles using MNG metamaterial
- An investigation on the effect of bending of Split Ring Resonators
- An investigation on the effect of bending on UC-PBG structures
Similar Researchers
Based on overlapping research topics
Samuel B. Fernandes
University of Arkansas at Fayetteville
Machine Learning Applications
Bioinformatics and Genomic Networks
Plant Physiology and Cultivation Studies
Jorge A. da Silva
Arkansas Agricultural Experiment Station
Bioinformatics and Genomic Networks
Plant Physiology and Cultivation Studies
Metabolism and Genetic Disorders
Zhan Su
University of Arkansas for Medical Sciences
Machine Learning Applications
Bioinformatics and Genomic Networks
Metabolism and Genetic Disorders
Argelia Lorence
Arkansas State University
Bioinformatics and Genomic Networks
Plant Physiology and Cultivation Studies
Metabolism and Genetic Disorders
Dotun Olaoye
University of Arkansas at Fayetteville
Machine Learning Applications
Bioinformatics and Genomic Networks
Plant Physiology and Cultivation Studies
Thomas K. Teoh
Arkansas State University
Plant Physiology and Cultivation Studies
Metabolism and Genetic Disorders
Plant Stress Responses and Tolerance