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Department of Biology College of Arts and Sciences

Shahid M. Mukhtar

Shahid M. Mukhtar

Adjunct Professor smukhtar@uab.edu

Research and Teaching Interests: Systems Biology, Network Science, Functional Genomics, Bioinformatics, Deep/Machine Learning using Animal and Plant Models

Office Hours: By appointment

Education:

Dr. Mukhtar conducted his Ph.D. research on Arabidopsis transcriptional regulatory networks at the Max Planck Institute in Cologne, Germany under the supervision of Dr. Imre Somssich. He was fortunate to continue his postdoctoral research in the laboratory of Dr. Jeff Dangl, a Howard Hughes Medical Institute investigator and a member of the National Academy of Sciences, at the University of North Carolina at Chapel Hill. He employed genomics, bioinformatics and computer-aided systems-level analyses to generate the first large-scale Arabidopsis-pathogens protein-protein interaction network in collaboration with the Dana Farber Cancer Institute and Center for Cancer Systems Biology, an affiliate of Harvard Medical School in Boston, MA. His four year post-doc fellowship resulted in a first author publication in Science (The Arabidopsis-pathogens interactome; Mukhtar et al. Science 2011), as well as a number of co-authored high impact papers, including another large-scale network assembly (the Arabidopsis interactome map; Science 2011), global mapping of the G-protein interactions (Molecular Systems Biology 2011) and sequencing and assembly of 19 strains of pathogenic bacterium P. syringae using next-generation sequencing approaches (PLoS Pathogens 2011).

Dr. Mukhtar joined UAB as a faculty member in 2010. During his period at UAB, Dr. Mukhtar had a strong track record of mentoring students who won awards and scholarships, including the Rising Star Award from UAB National Alumni Society, NSF Graduate Research Scholar Program fellowship, Ireland Research Travel Scholarship, Biology Outstanding Student Development Award, CAS Dean's Outstanding Student Award and CAS Dean's scholarship, and various awards for poster and oral presentations at UAB EXPO, regional and national meetings/conferences. Additionally, he was recognized with a number of teaching awards, including the 2021 UAB President's Award for Excellence in Teaching, and the 2021 CAS Dean's Award for Excellence in Teaching. While at UAB, Dr. Mukhtar was given a secondary faculty appointment in the Department of Surgery at UAB School of Medicine as well as appointed as a Scientist at the Nutrition and Obesity Research Center and a member of the Program of Immunology at SOM. He had collaborations that led to joint research publications and active grant funding from NIH as co-investigator in the departments of Dermatology and Neurobiology at UAB SOM. His interdisciplinary and cross-disciplinary experience includes a record of 62 peer-reviewed manuscripts (Shahid Mukhtar Google Scholar). In 2024, Dr. Mukhtar accepted a faculty position at Clemson University and was appointed as an adjunct professor at UAB.

Dr. Mukhtar’s research focuses on the interface of bioinformatics and life sciences. He is broadly interested in interdisciplinary research projects focused on genomics/systems biology using computational and deep learning approaches in diverse models. He aims to understand how macromolecular networks are organized in the cells and how pathogenic or disease-associated cues perturb such networks. Specifically, in Arabidopsis, his laboratory uses machine/deep learning approaches to identify gene function of novel ORFs in plant pathology and plant physiology. His laboratory generates large-scale datasets of macromolecular interactions and studies them by applying mathematical modeling, bioinformatics, and computational tools, both existing and developed in-house, to decipher the network structure, topological properties of the interactions, and ultimately extract new biological information.

Currently, Dr. Mukhtar is funded by two NSF awards as the PI. IOS-1557796 ($800,000) is focused on understanding the manipulation of sugar regulatory networks by pathogens. The second award NSF grant (IOS-2038872; $1,027,270), which employs artificial intelligence (machine and deep learning approaches) to predict functions of micro- and macronutrients in plants.

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