Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Assist Prof Dr. Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Biomedical, University of Texas at San Antonio, United States

Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio with a joint appointment in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME). His research focuses on developing AI models for disease phenotype prediction, biomarker identification, and generating explainable mechanisms of disease progression. Dr. Flores has pioneered several genomics and AI-based tools integrating spatial transcriptomics and Electronic Health Records (EHR) to characterize tumor microenvironments. πŸ’»πŸ”¬

Publication Profile

ORCID

 

Education:

πŸŽ“ B.S. in Electronics Engineering (Instrumentation) – Metropolitan Autonomous University, 2002. M.S. in Applied Mathematics – University of Texas at San Antonio, 2010. Ph.D. in Electrical Engineering (Computational Biology) – University of Texas at San Antonio, 2015

Experience:

Dr. Flores is an Assistant Professor at the University of Texas at San Antonio since 2020. He has previously held roles as a Postdoctoral Fellow at the National Institutes of Health (NIH) and as a Research Associate at the Greehey Children’s Cancer Research Institute. His expertise spans computational biology, bioinformatics, AI, and deep learning. He has contributed significantly to spatial biology and immuno-oncology, tackling diseases using innovative AI techniques. πŸ§¬πŸ€–

Research Focus:

Dr. Flores’ research delves into AI-driven disease modeling, integrating single-cell RNAseq, EHR, and RNA FISH imaging to study tumor microenvironments. His lab develops tools that predict disease gene dependence and identify dysregulated regulatory elements during disease progression. His ongoing work integrates AI with spatially resolved transcriptomics to study cancer and other complex diseases. πŸ”πŸ§ 

Awards and Honors:

πŸ… NIH Functional Peripheral and Central Vagal Neural Circuits Grant (PI), 2023-2025. Artificial Intelligence/Machine Learning Consortium Hub Specific Pilot Grant (PI), 2023-2025. Keystone Symposia Investigator Travel Award, June 2023

Publications Top Notes:

New tools for spatial biology transcriptomics & proteomics in immuno-oncology – Immuno-Oncology Insights (2023) DOI: 10.18609/ioi.2023.005
Cited by 5 articles.

Looking at the TMEs from the Spatial Transcriptomics Perspective – Advances in Cancer Research and Clinical Imaging (2022)
Cited by 8 articles.

Poster: The Tumor microenvironment of NSCLC – Keystone Symposia (June 2023)
Presented at Keystone Symposia on Single Cell Biology.

Dr. Mir Asif Iquebal | Bioinformatics and Computational Biology | Best Researcher Award

Dr. Mir Asif Iquebal | Bioinformatics and Computational Biology | Best Researcher Award

Dr. Mir Asif Iquebal, ICAR-Indian Agricultural Statistics Research Institute, India

Dr. Mir Asif Iquebal is a distinguished academician with a Ph.D. in Agricultural Statistics earned in 2008 from ICAR-Indian Agricultural Research Institute, New Delhi, India πŸŽ“. His doctoral expertise lies in advanced statistical methods, showcased in his thesis, β€œA Study on Some Nonlinear Time-series Models in Agriculture.” Prior, he excelled, securing the first rank in M.Sc. Agricultural Statistics in 2004, focusing on β€œEstimation of Heritability of Threshold Characters Using Auxiliary Traits.” Dr. Iquebal’s commitment to excellence in agricultural statistics is evident throughout his educational journey. With over sixteen years of extensive experience, he currently serves as a Senior Scientist at the Division of Agricultural Bioinformatics, ICAR-IASRI, contributing significantly to Computational Biology and Statistical modeling 🌐. His diverse professional background includes roles at ICAR-Indian Institute of Pulses Research, Kanpur, and ICAR-National Academy of Agricultural Research Management, Hyderabad. In teaching, spanning twelve years, he imparts knowledge to M.Sc. and Ph.D. students, covering a range of courses from Introduction to Bioinformatics to Computational Genomics πŸ“š. Dr. Iquebal’s research interests at the forefront of Computational Biology and Agricultural Bioinformatics involve Genomics, Genome Assembly, and RNA-seq Data Analysis. His innovative spirit extends to the application of Machine Learning techniques and the development of web-based tools, reflecting his dedication to advancing research accessibility in genomics and computational biology 🧬.

πŸŽ“ Education :

Dr. Mir Asif Iquebal is an accomplished academician with a Ph.D. in Agricultural Statistics earned in 2008 from ICAR-Indian Agricultural Research Institute, New Delhi, India πŸŽ“. His doctoral thesis, β€œA Study on Some Nonlinear Time-series Models in Agriculture,” reflects his expertise in advanced statistical methods. Prior, he secured the first rank in M.Sc. Agricultural Statistics in 2004 from the same institute, with a thesis on β€œEstimation of Heritability of Threshold Characters Using Auxiliary Traits.” Dr. Iquebal’s educational journey showcases his commitment to excellence in the field of agricultural statistics 🌾

🌐 Professional Profiles :

Scopus

Google Scholar

Orcid

πŸ”„ Experiences :

With over sixteen years of extensive experience, Dr. Mir Asif Iquebal is currently serving as a Senior Scientist at the Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute (IASRI), New Delhi 🌾. He has been contributing significantly since joining on April 11, 2011, engaging in impactful research in Computational Biology and Statistical modeling. His responsibilities encompass research, teaching, and training in the fields of Agricultural Bioinformatics, Computational Biology, and Agricultural Statistics. Prior to his current role, Dr. Iquebal worked at ICAR-Indian Institute of Pulses Research, Kanpur, and commenced his career as a Scientist at ICAR-National Academy of Agricultural Research Management, Hyderabad, in January 2008 πŸš€. His diverse experience underscores his expertise and commitment to advancing agricultural research and bioinformatics.

πŸ” Teaching :

Dr. Mir Asif Iquebal brings a wealth of teaching experience, spanning twelve years from 2011 to the present, imparting knowledge to M. Sc. and Ph. D. students at the PG School, ICAR-Indian Agricultural Research Institute, New Delhi πŸŽ“. His diverse range of courses reflects his expertise, including foundational subjects such as Introduction to Bioinformatics and Statistical Methods for Applied Sciences, as well as specialized topics like Computational Genomics and Machine Learning Techniques in Bioinformatics. Dr. Iquebal’s commitment to education is evident in the breadth of subjects he covers, contributing significantly to the academic growth of students in the field of agricultural bioinformatics and computational biology 🌱.

🌐 Research Interests  :

Dr. Mir Asif Iquebal’s research interests lie at the intersection of cutting-edge fields, focusing on Computational Biology and Agricultural Bioinformatics 🧬. His expertise encompasses Genomics, Genome Assembly, and RNA-seq Data Analysis, where he employs advanced techniques to unravel the complexities of biological data. Driven by innovation, he delves into the application of Machine Learning techniques for insightful data interpretation. Additionally, he contributes to the development of web-based tools and genomic resources, reflecting his commitment to advancing research accessibility and technological solutions in genomics 🌐.

πŸ“š Publication Impact and Citations :

Scopus Metrics:

  • πŸ“ Publications: 142 documents indexed in Scopus.
  • πŸ“Š Citations: A total of 954 citations for his publications, reflecting the widespread impact and recognition of Dr. Mir Asif Iquebal’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 1657 πŸ“–
    • h-index: 21  πŸ“Š
    • i10-index: 57 πŸ”
  • Since 2018:
    • Citations: 1304 πŸ“–
    • h-index: 17 πŸ“Š
    • i10-index: 43 πŸ”

πŸ‘¨β€πŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. πŸŒπŸ”¬

Publications Top Notes  :

1.  RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat

Journal: Scientific Reports, 9(1), 13917

Published Year: 2019

Cited By: 65

2.  Origin, diversity and genome sequence of mango (Mangifera indica L.)

Journal: Not Available

Published Year: 2016

Cited By: 65

3.  Uncovering genomic regions associated with 36 agro-morphological traits in Indian spring wheat using GWAS

Journal: Frontiers in Plant Science, 10, 527

Published Year: 2019

Cited By: 59

4.  Genetic variability for chickpea (Cicer arietinum L.) under late-sown season

Journal: Legume Research – An International Journal, 35(1), 1-7

Published Year: 2012

Cited By: 55

5.  Transcriptomic signature of drought response in pearl millet (Pennisetum glaucum (L.) and development of web-genomic resources

Journal: Scientific Reports, 8(1), 3382

Published Year: 2018

Cited By: 51