THE HERBOLD COMPUTATIONAL BIOLOGY PROGRAM -- Member Track Faculty
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Martin McIntosh, PhD

Full Member, Program Head

Lab website


 

 

 

Georg Luebeck, PhD

Full Member

Dr. McIntosh's group focuses on identifying the role of transcriptional and translational changes in cancer that lead to the formation of tumor antigens, primarily in ovarian and lung cancer. The primary goal is to identify new tumor antigens and develop them for use in diagnostics, prevention, imaging, and/or therapy.

The group's computational and wet-lab expertise has been in the use or development of a variety of RNA-sequencing and bioinformatics approaches to evaluate splicing events (using mRNA sequencing) and their translation (using ribosome profiling) in cancer tissues. The figure below shows an example that associates previously identified tumor antigens in ovarian cancer (primarily CT antigens) and those that are potential tumor antigens; coding sequences identified by mRNA sequencing that have also been found to be bound to translating ribosomes, and which have never been previously observed in somatic tissues. Those in the figure represent the subset of our candidates that we find are associated with the CT antigens concordantly across most tumors. These and other classes of potential cancer selective proteins are evaluated in our laboratory using a variety of targeted assays to evaluate their potential in a number of clinical uses.


The main research interest of Dr. Luebeck's team is the development of bio-mathematical descriptions of carcinogenesis, primarily in colon, lung, pancreas and esophagus. With this comes the identification and characterization of relevant spatio-temporal scales and their impact on cancer incidence. From these descriptions Dr. Luebeck has derived quantitative methods for the analysis of both experimental and epidemiological data, including data on precursor lesions from screening studies.

The ultimate goal is to be able to model/optimize the benefits of cancer screening, prevention, and intervention - based on a biological description of the natural history of cancer. For more information on these subjects, visit NCI CISNET.



Dr. Harlan Robins

 

 

 

Harlan Robins, PhD

Associate Member

Dr. Jesse Bloom

 

 

Jesse Bloom, PhD

Assistant Member, Joint with Basic Sciences

Lab website

Dr. Robins focuses on the quantitative analysis of the adaptive immune system. His approach takes advantage of new high-throughput sequencing technology developed by Dr. Robins and his collaborators. His group is isolating and sequencing millions of adaptive immune receptor rearrangements to profile the adaptive adaptive immune system. With this new technology, he is working toward a comprehensive description of the t-cell repertoire and studying the dynamics of immune response. He is applying this technology in multiple clinical settings including HSC transplant, Mulitple Sclerosis, Type 1 Diabetes, cancer immunotherapy, and vaccine development.

Dr. Bloom's group studies the molecular evolution of proteins and viruses. Most of this work focuses on influenza. One major goal is the development of combined computational and experimental approaches for leveraging the information contained in sequence databases to address questions in evolutionary biology, virology, and immunology. A second goal is to understand the factors that constrain and drive molecular evolution, in order to enable more effective viral forecasting.  Finally, the group works to develop therapeutics that target viruses in ways that block their usual routes of evolutionary escape.




 

 

 

Phil Bradley, PhD

Associate Member


 

 

Robert Bradley, PhD

Assistant Member, Joint with Basic Sciences

Lab website

Dr. Bradley’s group develops predictive models of molecular recognition using high-resolution structural modeling. His current focus is on predicting the specificity of protein-DNA and protein-peptide interactions. He is also one of the leaders of the development and application of new algorithms for molecular modeling within the framework of the Rosetta software package, a set of tools for the prediction and design of protein structures and interactions.


We study many different disorders—-from muscular dystrophy to cancer-—where RNA processing plays important roles in disease initiation and therapeutic response. In the long term, we seek to identify new biological phenomena that inform the development of improved treatments and therapeutics.



Dr. Erick Matsen

 

 

 

Erick Matsen, PhD

Assistant Member

Lab website

Dr. Raphael Gottardo

 

 

 

Raphael Gottardo, PhD

Associate member, Joint with VIDD

Lab website

The Matsen group proves theorems, develops algorithms, and writes code to understand problems in biology. We have a special interest in evolution and phylogenetics. At Fred Hutch, our work has focused on studying viral evolution, the human microbiome, and the immune system.


Dr. Gottardo is an investigator with a background in computational biology and statistics, specializing in applied statistical and computational genomics through interdisciplinary collaborations with biomedical and health researchers. He has been involved in some of the early statistical work in the area of gene expression microarrays, whole genome chip-chip and tiling arrays, next generation sequencing, and flow cytometry. See the image on the right for an application of Dr. Gottardo's research in flow cytometry on the discovery of sub-populations on a lymphoma sample.

Dr. Gottardo is currently working with researchers in the Vaccine and Infectious Disease Division to develop novel computational methods and tools that will be used to better understand the immune system responses relevant to vaccine development and evaluation. 




 

 

 

Trevor Bedford, PhD

Assistant Member, Joint with VIDD

Lab website

Dr. Paul Edlefsen

 

 

 

Paul T. Edlefsen, PhD

Assistant Member, Joint with VIDD

Dr. Bedford investigates the evolutionary and epidemiological dynamics of RNA viruses, focusing primarily on influenza virus and HIV. His work integrates population genetics, phylogenetics and epidemiological modeling to understand patterns of virus evolution, immune escape and geographic circulation. This work has a strong statistical and computational basis, using sequence and serology data to arrive at an understanding of hidden underlying processes. A thorough understanding of evolutionary and epidemiological processes contributes to successful surveillance, control and vaccination strategies. 


Dr. Edlefsen works primarily on statistical and computational models of genomic sequences. In particular, he has developed methods for using Profile Hidden Markov Models to represent highly varying sequence families, with applications to transposon and viral sequences, as well as methods for Bayesian and frequentist evaluation of pathogens infecting subjects of clinical trials ("sieve analysis"). Dr. Edlefsen is a clinical trials biostatistician for the HIV Vaccine Trials Network and is Director of the Computational Biology Core of the Vaccine and Infectious Disease Division, where his primary application focus is HIV vaccine genomics.