Collaboratorium Postdoctoral Researchers
Postdoctoral Researcher, Epidemiological/Biostatistical Modeling
Jake Ferguson is the Collaboratorium Epidemiological/Biostatistical Modeling Postdoctoral Researcher. Jake is directly responsible for modeling related to Project 1 and Project 2 and also works collaboratively with other staff postdocs on CMCI projects coming into the modeling core from other members of the University of Idaho biomedical community.
Jake has experience with a range of empirical modeling approaches from traditional statistical analyses to data-driven stochastic models. His past work has primarily utilized observational data, though he has experience with experimental data as well. He uses traditional applied mathematics tools such as differential equations and dynamical systems. Most of his work has been on problems that develop process models in order to explore the general properties of systems, but he also has worked in developing complex data-driven models. The questions and available data ultimately dictate the approach he uses.
Postdoctoral Researcher, Molecular Modeling
Jagdish Patel is the Collaboratorium Molecular Modeling Postdoctoral Researcher. Jagdish is directly responsible for molecular modeling related to Project 1 and Project 2 in the area of viral co-infection and host interactions; and also works collaboratively with other staff postdocs on CMCI projects coming into the modeling core from other members of the University of Idaho biomedical community.
Jagdish uses molecular dynamics and enhanced sampling techniques for studying “rare events” such as protein-ligand interactions, protein-protein interactions, folding/unfolding, and ion transfer via protein channels. He has experience in protein structure prediction using homology modeling, sequence analysis, modeling drug-target interactions using docking, virtual screening of libraries of small molecules against its target to identify ‘hits’ and prediction of their physio-chemical properties. He also performs free energy calculations to test the effects of mutations on molecular structure and is developing new approaches for calculating free energy with speed & accuracy and molecular dynamics simulations of systems involving protein, DNA, and RNA molecular models.
JT Van Leuven
Postdoctoral Researcher, Omics Analysis and Modeling
JT Van Leuven is the Collaboratorium Transcriptomic/Proteomic Modeling Postdoctoral Researcher. JT is directly responsible for gene expression modeling related to Project 1 and Project 2 provides expertise in proteomics; and also works collaboratively with other staff postdocs on CMCI projects coming into the modeling core from other members of the University of Idaho biomedical community.
JT has a background in molecular biology and evolution. As a wet-lab molecular biologist, he has experience in protein/nucleic acid purification and quantification, nucleic acid manipulation, cell culture, and viral vector production. As a bioinformatician, he is familiar with analyzing NGS datasets to do genome/transcriptome assembly, differential expression analysis, and SNP quantification. In the past, he has used these methods to show how the nutritional symbionts of sap-feeding insects depend on their hosts. He is particularly interested in projects that improve our understanding of host-microbe and microbe-microbe interactions, including how these interactions influence the evolution of the partners. JT Van Leuven’s Website.
Project Postdoctoral Researchers
Md. Bahadur Badsha
Currently, Dr. Badsha is working as a postdoctoral researcher with Dr. Audrey Qiuyan Fu in the Externally Funded CMCI Project “Causal Inference of Gene Regulatory Networks with Application to Breast Cancer” at the University of Idaho. A major interest in genome research is the proper understanding of the mechanisms of gene regulation, as well as the generation of phenotypes and the physiology of diseases, which can begin to go beyond interactions and to establish the cause-effect relationships (causality) the among interacting genes. Generally, experimental interference is used to find these relationships. However, most of the time experiments are infeasible because of time, cost or ethical constraints. Statistical causal inference methods as a complementary approach to experimental methods. Therefore, in this project, Dr. Badsha is working on developing a machine learning approach which can be applied to genotype and gene expression data and efficiently learn a causal graph of genes from breast cancer data.
After finishing my PhD. from the Department of Bioscience and Bioinformatics at Kyushu Institute of Technology (Kyutech), Japan, Dr. Badsha worked as a postdoctoral researcher at Kyutech and we focused metabolic analysis of antibody producing Chinese hamster ovary cell culture under different stresses conditions. He also worked as a lecturer at the Department of Mathematics and Natural Science (MNS), BRAC University, Bangladesh, in 2012. His research interests are; Statistical Genomics and Bioinformatics, Computational Biology, Systems and Synthetic Biology and Metabolic Engineering.
Postdoctoral Researcher, Department of Mathematics
Andrew is a postdoctoral researcher, he did his Ph.D. work with Fred Adler at the University of Utah where he used mathematical models to study ant behavior. Currently, he is working on developing mathematical models that evaluate the efficacy of transmissible vaccines. He is working with Scott L Nuismer in his lab and with working group Transmissible Vaccines (TransVax) at CMCI.
Postdoctoral Researcher, Department of Mechanical Engineering
Rabijit has an interest in developing computational fluid dynamic models for complex flows of engineering and natural relevance. Rabijit Dutta has worked in understanding fluid turbulence in hydraulic turbines and jet impinging flows using supercomputers. He is currently working with Tao Xing on his project Multi-scale Model of Interactions between Lung and Pulmonary Ventilation. Where he is working on developing a multi-scale model for understanding the interaction between respiratory gas exchange and pulmonary ventilation.
Postdoctoral Researcher, Aberdeen Research & Extension Center
Andrea Gonzalez-Gonzalez is the Postdoctoral Researcher for Project 2 multi-level Dynamics of Viral Co-Infection. She is studying the effects of viral co-infection in fruit flies (Drosophila melanogaster); analyzing viral growth dynamics using quantitative real-time PCR in adult flies infected with one or two viruses (Drosophila C Virus C and Drosophila Virus X); and will be examining host gene expression in uninfected and infected flies.
Postdoctoral Researcher, Department of Statistical Sciences
Rui Li is working as a postdoctoral researcher on Dr. Audrey Fu project Causal Inference of Gene Regulatory Networks with Application to Breast Cancer. His current research focus is combining deep learning with sequencing data analysis. Rui Li came with a wet-lab background of biotechnology during his bachelor’s training, and preventive veterinary medicine during his master’s training. During his Ph.D., he shifted to bioinformatics, working on improving the 3’UTR annotation of Xenopus tropicalis, and the alternative polyadenylation phenomenon. His skill set includes Perl programming, NGS data analysis, and machine learning techniques.