Data Science: Pre & Postdoctoral Training

I joined King Abdullah University of Science and Technology to start my Ph.D. study in 2010. I was a member of the Structural and Functional Bioinformatics group, led by Prof. Xin Gao. My research focus was on determining the 3D structures of proteins using Nuclear Magnetic Resonance (NMR) data. My research during Ph.D. resulted in five journal papers published in Bioinformatics, Plos One, Journal of Biomolecular NMR, Scientific Reports, and IEEE/ACM Transactions on Computational Biology and Bioinformatics.

In 2017, I started my first postdoctoral training. I joined the group of Prof. Jianyang Zeng in Institute for Interdisciplinary Information Sciences, Tsinghua University. Prof. Zeng gave me all the trust and freedom to do proper research. He suggested me a very promising research topic about 3D genome modeling using Hi-C and FISH data. My work in this project resulted in a Nature Communications paper that was published earlier this year (2019). Also, I worked on another related project about 3D genome modeling using single-cell Hi-C data. This second project gave good results, and its manuscript is still under preparation.

Dr. Amin received his Ph.D. in cancer computational biology from Baylor College of Medicine, Houston, TX in 01/2017. His thesis work was carried out at the UT MD Anderson Cancer Center, and was focused on understanding long non-coding RNA interactions in the context of chromatin organization using integrated analyses of publically available expression, epigenomic and chromatin interaction data. Before completing Ph.D., Dr. Amin received research training (2008-2011) in computational biology at the Dana-Farber Cancer Institute, Boston, MA where he worked on the assessment of gene expression profiling as predictive biomarker in multiple myeloma. Previously, Dr. Amin received his first professional degree in medicine, MBBS from the Medical College of Maharaja Sayajirao University of Baroda, Vadodara, India in 2005.

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Dr. Barthel received his M.D. degree from the Vrije Universiteit Amsterdam prior to joining the MD Anderson Cancer Center in Houston to pursue a postdoctoral position in glioma genomics. He research is focused on transcriptional and epigenetic profiling of gliomas and in understanding the genomic basis of telomere maintenance in cancer.

I integrate operant and classical conditioning paradigms with modern systems genetics techniques to identify the genetic and genomic mechanisms underlying fundamental behavioral processes driving drug addiction and related behavioral disorders.

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My job is to use bioinformatics tools to understand gene and protein expression in the aging heart.

I received my Ph.D. in Biochemistry and Molecular Biology from Huazhong Agricultural University where I studied the genetic and biochemical bases of rice metabolome variation by an approach combined genomics, genetics and metabolomics. Previously, I received my B.S. in Biological Science at Huazhong Agricultural University. After getting my Ph.D., I joined Dr. Wei Chia-Lin’s lab at DOE Joint Genome Institute, working on the epigenetic control of drought response in sorghum.

Currently I am a postdoctoral associate in our Genome Technologies group. My researches focus on developing ultra-long read sequencing methods with the third generation single-molecule sequencing technologies and applying them with other cutting edge genome technologies to identify the genomic structural variations in cancer genome.

I joined the Simon John lab in the spring of 2013, excited by the opportunity of working with Dr. John and using a multidisciplinary approach in my research. Using DBA/2J mice as a model of glaucoma, my current research focuses on axon degeneration, the role of innate immunity in the central nervous system, and the role of diet in neurodegeneration. This includes studying the role of JNKs in glaucomatous injury and working to identify early signaling events that may initiate injury. For another project, I am collaborating with faculty from Dalhousie University, working on defining human genes responsible for exfoliation syndrome glaucoma. I also work closely with fellow postdoc Pete Williams and help direct two research assistants in the lab.  This opportunity to collaborate and manage while working through complex projects is broadening my conceptual thinking abilities both scientifically and managerially, and improving the array of skill sets necessary for running a lab.

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Dr. Johnson has a Ph.D. in Experimental and Molecular Medicine from Dartmouth where he received comprehensive training in quantitative and basic biomedical sciences. He has strong interest in the dynamic epigenomic landscape of glioma cells during disease progression and recurrence.

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Dr. Johnson has a PhD in nutritional ecology and completed a career development fellowship in computational genomics before joining the Weinstock Lab. His interest is in leveraging next-generation sequencing technologies to study how environmental factors, such as nutrition, influence host-microbiome interactions at a functional genomic level.

I completed my undergraduate studies in Biotechnology at IIT Roorkee, India. This was followed by a project in the Axon Regeneration Lab at IISc Bangalore, under Dr. Ramanan's supervision. I am currently a Graduate Assistant in the Stitzel and Ucar lab at JAX-GM.

I've brought my background in synthetic biology to the Oh Lab with the aspiration to leverage the human microbiome (the bacteria, fungi, viruses, and other microbes that live on us) to promote health, prevent infections, and treat diseases. Here I have been engineering Staphylococcus epidermidis, a ubiquitous skin commensal, to detect and kill pathogens, as well as secrete therapeutics. Additionally, I have been conducting a sizable clinical metagenome study investigating the relationship between aging, health, and the microbiome. This study should help us understand how we can leverage the microbiome to promote healthy aging, combat chronic illnesses, and prevent infections commonly acquired by older adults in healthcare settings. Finally, I have been exploring the use of human skin explants and stem cell derived skin “organoids” to model human skin microbiome interactions. This will allow us and others to test engineered skin microbiome therapeutics, and better identify mechanisms by which the skin microbiome modulates health and disease.

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Genetic diversity is key for survival especially in the phase of continuous environmental changes. My current research leverages whole-genome sequences from wild-caught mouse species representing the repertoire of diversity, to discover patterns of variations that give rise to genetic diversity. By focusing on introgression, positive selection and balancing selection, my goal is to detect the footprint of these genomic signatures and their evolutionary roles in mammalian genome.

  View Raman Lawal on Research Gate 

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I was admitted to Xi'an Jiaotong University at the age of 15. And I received my B. S., and Ph.D. degrees from Xi'an Jiaotong University, China in 2004, and 2010, respectively. Before I worked in Blekinge Institute of Technology, Sweden and Zhengzhou University, China. I have published more than 15 journal and conference papers in the areas of machine learning with uncertainty, E-Health system and DNA computing.

At JAX, I engaged in multi-omic data analysis and algorithm development, including epigenetic pattern mining and algorithm development of cancer, and DNA methylation pattern mining research.

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Dr. Liu received his Ph.D. in chemical biology from University of Pittsburgh, Pennsylvania, in 2017. Prior to that, he received his B.S. in bioinformatics from Huazhong University of Science and Technology, China, in 2011. His current research interest is to apply genetic and genomics techniques to study mechanisms of brain tumor evolution.

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I am a systems Immunologist working in the field of dendritic cells biology. My research focuses on understanding how epigenetic and/or transcriptional modifications occurring in immune-cell populations orchestrate and modulate the quality of the immune response to different type of antigens including pathogens, auto-antigens and vaccines. To try to answer these challenging questions, we are employing a multidisciplinary approach, combining computational methods and cell biology.

Develops computational approaches using phenotype data to identify complex genetic networks and gene interactions relevant to AD.

I am a graduate student in Biomedical Sciences in Uconn Health with the supervisor of Dr. Sheng Li. I am interested in applying machine learning and advanced statistical modeling into biological questions.

I am mainly interested in how regulatory and epigenetic factors can influence the inheritance and expression of heritable traits, especially complex traits. My Ph.D. work primarily used human genetic methods, and I joined The Jackson Laboratory to expand my expertise with mice. My current research involves the role of the histone methyltransferase PRDM9 in allocation and repair of meiotic double-strand breaks, which are necessary for the essential process of genetic recombination. In mammals, PRDM9 is responsible for both initiating and localizing the sites of recombination within the genome. I have several ongoing projects in the lab, all of which involve the DNA-binding properties of PRDM9 in vivo, and the roles of PRDM9-dependent histone modifications in recombination.

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Developing deep learning algorithms including graph embedding and link prediction techniques in knowledge graphs constructed from networks of genes, drugs and diseases to predict new treatments for diseases.

Implementing machine learning algorithms to analyze immune profiling and clinical data of patients with chronic fatigue syndrome.

Implementing methods for translational bioinformatics with a focus on whole exome and whole genome sequencing.

Dr. Sordo Vieira joined The Jackson Laboratory in July 2018 to work in the Laubenbacher laboratory as a postdoctoral associate. His main interests lie in cancer systems biology. He is particularly interested in multi-scale mathematical modeling incorporating genetic and epigenetic data to investigate the role of iron and the tumor microenvironment on cancer progression. He was previously a postdoctoral fellow for one year at UConn Health's Center for Quantitative Medicine working on mathematical analysis of intracellular signaling networks.

As a graduate student at the University of Kentucky, Dr. Sordo Vieira received the prestigious National Science Foundation Graduate Student Fellowship and proved a major part of an old number theoretic conjecture. He graduated Summa Cum Laude from Wayne State University in 2012 with a B.S. in Mathematics and a minor in physics.

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The purpose of my research at the Ching Lau Lab is to examine genomic and epigenomic data from pediatric cancers in order to discover molecular phenotypes, prognostic biomarkers, and candidate therapeutic targets. My work includes method and pipeline development for integration of multi-omic data in the analysis of pediatric brain and bone tumors to develop a better molecular understanding of these often-lethal cancers. Currently, my research focuses on osteosarcoma, ependymoma, and intracranial germ cell tumors.

In 2013, I graduated from the College of the Holy Cross where I had work with Dr. Kenneth Mills on studying protein splicing. After college, I worked as a research assistant in Dr. Rameen Beroukhim's lab at the Dana-Farber Cancer Institute. In the Beroukhim lab, I worked with graduate student, William Gibson, and postdoctoral fellow, Brenton Paolella on validating the splicing factor SF3B1 as a CYCLOPS gene. In 2015, I began the University of Connecticut MD/PhD program, and joined the Anczukow lab in 2017.

Dr. Varn received his Ph.D in Molecular and Systems Biology from Dartmouth College in 2018. While at Dartmouth, his thesis work focused on developing and applying computational methods to investigate the factors influencing the immune response in different cancer types. As a postdoctoral associate at JAX, his research projects integrate his background in computational biology, cancer biology, and immunology to study how the immune response shapes brain tumor evolution.

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Anita, a joint postdoctoral fellow with the Oh and Weinstock groups, is most recently from Heidelberg, Germany, where she studied with Dr. Peer Bork and Dr. Magnus von Knebel Doeberitz on numerous microbiome projects related to colorectal cancer and methods development. She is interested in understanding the fundamental roles of the microbiome, particularly the skin and the gut microbiome, in health and disease.

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Dr. Zeeshan has a PhD in Bioinformatics and her research is aimed at understanding highly aggressive cancers. Associated with “The Cancer Isoform Program” in deciphering the basis of cancer with in-depth isoformic characterization of cancer cells leveraging modern genomic tools with the aim to develop novel therapeutic strategies for precision medicine. Her work is focused on transcriptome profiling of high-grade cancers such as triple negative breast cancer and melanoma that are characterized by a high level of genetic heterogeneity that are not responsive to targeted interventions. 

As immuno-oncology takes center stage in the battle against cancer, the need for biomarkers has become even more acute. Applying immunoinformatics to studying cancer biology, her work has led her to identify  alternative-splicing alterations in cancer and develop a quantitative, in-depth mechanistic understanding of molecular communication governing the dynamics of the tumorigenesis. Identification of novel signatures at various stages and with different treatments will serve as promising candidates for novel therapeutics as well as biomarkers for precise treatment and management.

Wei is broadly interested in evolution and ecology of microbes in complex communities using genomic methods. Before joining the Oh Lab, he worked with Dr. Dustin Brisson in the University of Pennsylvania to study host-microbe interaction and evolution of microbial pathogens. Presently he is developing computational tools that characterize microbes and microbial interactions more effectively and with less necessary domain expertise.

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