Email: hickeys6@msu.edu
Dr. Hickey earned her Ph.D. in neuroscience from the University of Texas Southwestern Medical Center in 2018 under the supervision of Dr. Genevieve Konopka. During her graduate training she investigated the role of language-related transcription factor FOXP2 in neural development using traditional molecular biology techniques, human and animal model systems, and next-generation sequencing approaches. As a computational biology postdoc at MSU in Dr. Arjun Krishnan’s group, Dr. Hickey leveraged her diverse training to collaborate with experimental biologists, building computational pipelines that integrate diverse data from multiple sources to answer complex biological questions. In 2021, Dr. Hickey was awarded a Brain and Behavior Research Foundation Young Investigator Grant to predict brain-region- and age-specific treatments for schizophrenia by integrating thousands of gene-expression studies using machine learning techniques. She is passionate about data visualization and making computational experiments easily reproducible.
Email: lindero1@msu.edu
Dr. Linderoth earned his PhD in Integrative Biology from the University of California, Berkeley, under the supervision of Dr. Rasmus Nielsen and Dr. Montgomery Slatkin, focusing on statistical and population genomic approaches for studying demographic histories, adaptive traits, and genomic regions refractory to short read assembly and mapping. Afterwards, he joined Dr. Richard Durbin’s group at the University of Cambridge as a Postdoctoral Research Associate to study the evolutionary radiation of East African cichlid fishes. Dr. Linderoth currently works as a Research Specialist at MSU’s W. K. Kellogg Biological Station mainly focused on population and conservation genomics with an emphasis on understanding how population size, connectivity, and management influences long-term viability and adaptive potential of at-risk species. He also focuses on developing computational methods for studying the genetic underpinnings of fitness-related traits and probabilistic approaches for population genetic inference from low-coverage sequencing data.
Email: longnany@msu.edu
Dr. Long received her Ph.D. in animal science (2011) and a master's degree in statistics (2009), both from the University of Wisconsin-Madison. Her thesis work centered around high-dimensional genetic marker data used for predicting genetic values of individuals. She published 15 peer-reviewed journal articles during her Ph.D. study, by investigating and developing a variety of statistical modeling methods to enhance the accuracy of genome-enabled prediction of quantitative traits. She then pursued a three-year postdoctoral training at Duke University School of Medicine, where she continued working on statistical methodology, with a focus on identifying causal variants using both sequencing data and array data. Before joining ICER in the summer of 2017, she was a statistical geneticist at the University of North Carolina-Chapel Hill School of Pharmacy and worked on Drug-Induced Liver Injury Network, an NIDDK-funded large-scale genetic analysis consortium. Currently, Dr. Long commits part of her time to providing bioinformatics services to researchers at MSU, in addition to supporting HPCC users.
Email: luyihkua@msu.edu
Dr. Yih-Kuang Lu received a PhD in the Plant Biology from the University of California at Davis, and later a Professional Science master’s degree in the Computational Biosciences from Arizona State University. After his graduation, he has been served as the post-graduate scholar on the study of the circadian rhythm regulated by cryptochrome; the research manager on the genome assembly of phototrophic bacteria living in various extreme environment funded by NSF; the biomed computational data analyst on conducting processing, managing, and analyzing the patient-oriented omics data which are collected from the hospitals throughout multiple research collaborations. He is an experienced bioinformatics analyst with 10+ years of experience in research. He possesses extensive knowledge of computational biology methods and has acquired multiple certificates in statistics and related analytics. He joined ICER in July of 2023 to provide bioinformatics services to all campus-wide researchers.
Email: panchyni@msu.edu
Dr. Panchy earned his Ph.D. in genetics from Michigan State University in the lab of Dr. Shin-Han Shiu, where his research focused on the application of bioinformatics and computational biology methods to understand gene expression in plant systems. After this, he was a postdoctoral research associate in the Department of Biochemistry & Cellular and Molecular Biology in the lab of Dr. Tian Hong at the University of Tennessee, Knoxville. His research focused on modeling and visualization approaches for understanding the progression of cellular differentiation processes, primarily epithelial to mesenchymal transition. Currently Dr. Panchy’s work focuses on promoting researchers and assisting investigators at MSU through both the Bioinformatics Core and the Institute for Cyber Enabled Research.