Computational Modeling Archives - Sanford Burnham Prebys (2024)

Related Disease
Cardiomyopathies, Cardiovascular Diseases

Anatomical Systems and Sites
Cardiovascular System, General Cell Biology, Heart

Research Models
Computational Modeling, Drosophila, Human

Techniques and Technologies
Bioinformatics, Cell Biology, Confocal Microscopy, Fluorescence Microscopy, Genetics, In vivo Modeling, Live Cell Imaging, Live Imaging, Microscopy and Imaging, Molecular Biology, RNA Interference (RNAi), Systems Biology, Transgenic Organisms

Related Disease
HIV/AIDS, Infectious Diseases, Molecular Biology

Phenomena or Processes
Host-Pathogen Interactions, Infectious Disease Processes, Inflammation, Innate Immunity

Anatomical Systems and Sites
Immune System and Inflammation

Research Models
Clinical and Transitional Research, Computational Modeling, Human, Human Cell Lines, Mouse, Mouse Cell Lines, Primary Cells, Primary Human Cells

Techniques and Technologies
Biochemistry, Bioinformatics, Cellular and Molecular Imaging, Drug Discovery, Drug Efficacy, Gene Expression, Gene Knockout (Complete and Conditional), Gene Silencing, High-Throughput/Robotic Screening, RNA Interference (RNAi), Systems Biology

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Showing 3 of 3

Education and Training

2010: Postdoctoral associate, Molecular Biophysics and Biochemistry, Yale University
2009: PhD, Computer Science, Yale University
2003: M.Phil., Computer Science, The University of Hong Kong
1999: B.Eng., Computer Engineering, The University of Hong Kong

Related Disease
Biliary Atresia, Cancer, Diabetes – General, Hirschsprung Disease, Liver Cancer, Nasopharyngeal Carcinoma, Type 2 Diabetes

Phenomena or Processes
Cancer Epigenetics, Gene Regulation, Oncogenes, Posttranslational Modification, Transcriptional Regulation, Tumor Microenvironment

Anatomical Systems and Sites
Endocrine System, General Cell Biology, Immune System and Inflammation, Liver

Research Models
Computational Modeling

Techniques and Technologies
Bioinformatics, Comparative Genomics, Genomics, Machine Learning, Protein-Protein Interactions, Systems Biology

We study gene regulatory mechanisms by means of computational modeling. To facilitate our data-centric approach, we develop novel methods for analyzing large amounts of biological data, including those produced by cutting-edge high-throughput experiments. Our computational models provide a systematic way to investigate the functional effects of different types of perturbations to regulatory mechanisms, which creates testable hypotheses for studying human diseases and facilitates translational research.

Google Scholar profile

F1000 Faculty profile

YouTube:Bioinformatics micro-modules

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Showing 3 of 3

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

Gerstein MB, Lu ZJ, Van Nostrand EL, Cheng C, Arshinoff BI, Liu T, Yip KY, Robilotto R, Rechtsteiner A, Ikegami K, Alves P, Chateigner A, Perry M, Morris M, Auerbach RK, Feng X, Leng J, Vielle A, Niu W, Rhrissorrakrai K, Agarwal A, Alexander RP, Barber G, Brdlik CM, Brennan J, Brouillet JJ, Carr A, Cheung MS, Clawson H, Contrino S, Dannenberg LO, Dernburg AF, Desai A, Dick L, Dosé AC, Du J, Egelhofer T, Ercan S, Euskirchen G, Ewing B, Feingold EA, Gassmann R, Good PJ, Green P, Gullier F, Gutwein M, Guyer MS, Habegger L, Han T, Henikoff JG, Henz SR, Hinrichs A, Holster H, Hyman T, Iniguez AL, Janette J, Jensen M, Kato M, Kent WJ, Kephart E, Khivansara V, Khurana E, Kim JK, Kolasinska-Zwierz P, Lai EC, Latorre I, Leahey A, Lewis S, Lloyd P, Lochovsky L, Lowdon RF, Lubling Y, Lyne R, MacCoss M, Mackowiak SD, Mangone M, McKay S, Mecenas D, Merrihew G, Miller DM 3rd, Muroyama A, Murray JI, Ooi SL, Pham H, Phippen T, Preston EA, Rajewsky N, Rätsch G, Rosenbaum H, Rozowsky J, Rutherford K, Ruzanov P, Sarov M, Sasidharan R, Sboner A, Scheid P, Segal E, Shin H, Shou C, Slack FJ, Slightam C, Smith R, Spencer WC, Stinson EO, Taing S, Takasaki T, Vafeados D, Voronina K, Wang G, Washington NL, Whittle CM, Wu B, Yan KK, Zeller G, Zha Z, Zhong M, Zhou X, modENCODE Consortium, Ahringer J, Strome S, Gunsalus KC, Micklem G, Liu XS, Reinke V, Kim SK, Hillier LW, Henikoff S, Piano F, Snyder M, Stein L, Lieb JD, Waterston RH

Science 2010 Dec 24 ;330(6012):1775-87

Dr. Yu Xin (Will) Wang received his PhD at the University of Ottawa where he identified cellular asymmetry and polarity mechanisms regulating muscle stem cell self-renewal and skeletal muscle regeneration. He then carried out postdoctoral training at Stanford University School of Medicine developing single cell multi-omic approaches to characterize the regenerative process and what goes awry with disease and aging.

“I’ve always had a passion for science and became fascinated with how the body repairs and heals itself when I was introduced to the potential of stem cells in regenerative medicine. I was struck by the ability of a small pool of muscle stem cells that can rebuild and restore the function of muscle. My lab at Sanford Burnham Prebys aims to better understanding the repair process and harness our body’s ability to heal in order to combat chronic diseases and even counteract aging.”

Education and Training

Postdoctoral Fellowship, Stanford University School of Medicine
PhD in Cellular Molecular Medicine, University of Ottawa, Canada
BS in Biomedical Sciences, University of Ottawa, Canada

Prestigious Funding Awards

2020: NINDS K99/R00 Pathway to Independence Award

Honors and Recognition

Governor General’s Gold Medal – Canada

Related Disease
Aging-Related Diseases, Amyotrophic Lateral Sclerosis (Lou Gehrig’s Disease), Arthritis, Cachexia, Inflammatory/Autoimmune Disease, Multiple Sclerosis, Muscular Dystrophy, Myopathy, Neurodegenerative and Neuromuscular Diseases, Sarcopenia/Aging-Related Muscle Atrophy, Spinal Muscular Atrophy

Phenomena or Processes
Adult/Multipotent Stem Cells, Aging, Cell Signaling, Development and Differentiation, Epigenetics, Exercise, Extracellular Matrix, Neurogenesis, Organogenesis, Regenerative Biology, Transcriptional Regulation

Anatomical Systems and Sites
Immune System and Inflammation, Musculoskeletal System, Nervous System

Research Models
Clinical and Transitional Research, Computational Modeling, Human Adult/Somatic Stem Cells, Mouse

Techniques and Technologies
3D Image Analysis, Bioinformatics, Cellular and Molecular Imaging, Gene Knockout (Complete and Conditional), Genomics, High Content Imaging, High-Throughput/Robotic Screening, Live Cell Imaging, Machine Learning, Microscopy and Imaging, Proteomics, Transplantation

The Wang lab is interested in elucidating critical cell-cell interactions that mediate the function of tissue-specific stem cells during regeneration and disease, with a focus on

  1. how a coordinated immune response can promote regeneration and
  2. how autoimmunity impacts tissue function and hinder repair.

Specifically, the Wang lab aims to identify cellular and molecular crosstalk between muscle, nerve, and immune systems to develop targeted therapies that overcome autoimmune neuromuscular disorders and autoimmune aspects of “inflammaging.”

Yu Xin (Will) Wang’s Research Report

The lab’s research is translationally oriented and utilizes interdisciplinary molecular, genetic, computational (machine learning and neural networks), and bioengineering approaches to view biology and disease from new perspectives. We combine multi-omics sequencing and imaging methods to resolve how different cell types work together after injury to repair tissues and restore function. We use a data-driven approach to identify targetable disease mechanisms and, through collaborations with other researchers and clinicians, develop therapies that promote regeneration. Visit our lab website to learn more.

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Dr. Xiao Tian participates in the Degenerative Diseases Program and the Cancer Genome and Epigenetics Program at Sanford Burnham Prebys. He started his lab in 2024 to understand the fundamental biology of aging and its contribution to age-related diseases. He joined the Institute after his postdoctoral research in Dr. David Sinclair’s lab at Harvard Medical School where he co-wrote the Information Theory of Aging. He obtained his BS from Shandong University and his PhD from the University of Rochester where he worked with Dr. Vera Gorbunova.

Education

2018-2023: Postdoc, Harvard Medical School
2016-2018: Postdoc, University of Rochester
2010-2016: PhD, Biology of Aging, University of Rochester
2005-2009: BS, Microbial Technology, Shandong University

Honors and Awards

2020-2026: K99/R00 Pathway to Independence Awards, NIH/NIA
2019-2020: NASA Postdoctoral Fellowship, NASA Ames Research Center
2017: Outstanding Dissertation Award for the Natural Sciences, University of Rochester
2015: Messersmith Dissertation Fellowship, University of Rochester
2014: Award for Outstanding Self-Financed Students Abroad, China Scholarship Council
2010-2014: Holtfreter Fellowship, University of Rochester
2007: Weichai Power Scholarship, Shandong University
2006-2008: Excellent Student Scholarship, Shandong University

Related Disease
Aging-Related Diseases, Alzheimer’s Disease, Cancer

Phenomena or Processes
Aging, Epigenetics, Genomic Instability, Neurodegeneration

Research Models
Computational Modeling, Mouse, Naked Mole Rat, Primary Human Cells

Techniques and Technologies
Bioinformatics, Epigenomics, Gene Expression, Gene Knockout (Complete and Conditional), High-Throughput/Robotic Screening, Mouse Behavioral Analysis

The Tian lab studies the fundamental mechanisms of aging and their roles in the onset of age-related diseases. Our recent research in epigenetic reprogramming and aging clocks indicates that the progressive loss of epigenetic information over time is a key driver of aging. The current research of the lab focuses on understanding how the epigenetic landscape is set up and maintained and investigating why the maintenance system fails which leads to aging and related diseases including cancer and neurodegeneration. Building on this, our ultimate goal is to develop safe and effective rejuvenation strategies to counteract aging.

Xiao Tian’s Research Report

Below are my major contributions to the field of aging research during my PhD and postdoc work:

Uncovering the first anti-cancer and longevity mechanism of the naked mole rat

We identified high-molecular-mass hyaluronan (HMM HA) as a critical mechanism for thecancer resistance of the naked mole-rat cells. Furthermore, we found that thisanti-cancer and longevity mechanism from naked mole rats can be integrated into other species, highlighting the significant implications of identifying new mechanisms from long-lived species. Our goal is to decipher how long-lived organisms control the pace of aging and deter age-related diseases.

Discovering enhanced DNA double-strand break (DSB) repair in long-lived species

Using a group of 18 species, we revealed thatlong-lived species possess efficient DNA double-strand break repair, mediated by potent SIRT6 activities. Future directions include deciphering how long-lived species address different types of cellular stress to maintain genomic and epigenomic stability.

Epigenetic reprogramming as a strategy to counteract aging and age-related diseases

We illustrated that epigenetic information loss as a result of DNA damage repair is akey driver of aging. One interventional strategy is to recover the lost epigenetic information, such as through reprogramming. We revealed that epigenetic reprogramming is an effective strategy to counteract aging and even potentiallymodify the trajectory of age-related diseases including glaucoma. We are currently testing other disease settings.

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Reprogramming to recover youthful epigenetic information and restore vision.

Lu Y, Brommer B, Tian X, Krishnan A, Meer M, Wang C, Vera DL, Zeng Q, Yu D, Bonkowski MS, Yang JH, Zhou S, Hoffmann EM, Karg MM, Schultz MB, Kane AE, Davidsohn N, Korobkina E, Chwalek K, Rajman LA, Church GM, Hochedlinger K, Gladyshev VN, Horvath S, Levine ME, Gregory-Ksander MS, Ksander BR, He Z, Sinclair DA

Nature 2020 Dec ;588(7836):124-129

Lukas Chavez is an Associate Professor at the Sanford Burnham Prebys. He is also the Director of the Clayes Research Center for Neuro-Oncology at the Institute for Genomic Medicine at the Rady Children’s Hospital, San Diego. In this role, he works with a team of physicians and scientists to capture genomic, transcriptomic, epigenetic and functional data from pediatric brain tumor patients, and uses this information to improve diagnosis and treatment. His research interests focus on structural variants as well as circular extrachromosomal DNA (ecDNA) in childhood cancers. These extrachromosomal DNA circles are frequently found in highly aggressive solid tumors and represent a new target for improved therapeutic approaches.

Education

2010: PhD, Free University, Berlin

Honors and Recognition

2020: St. Baldrick’s Scholar Award, St. Baldrick’s Foundation
2019: Award of Excellence in Pediatric Neuro-Oncology, Society of Neuro-Oncology
2012–2015: Feodor-Lynen Fellowship for Postdoctoral Researchers, Alexander-von-Humboldt Foundation

Related Disease
Brain Cancer, Cancer

Phenomena or Processes
Cancer Biology, Cancer Epigenetics, Chromosome Dynamics, Combinatorial Therapies, Gene Regulation, Genomic Instability, Oncogenes, Transcriptional Regulation

Anatomical Systems and Sites
Brain

Research Models
Clinical and Transitional Research, Computational Modeling, Cultured Cell Lines, Human, Human Cell Lines, Mouse

Techniques and Technologies
Bioinformatics, Cell Biology, Computational Biology, Computational Modeling, Gene Expression, Gene Silencing, Genomics, Single Nucleotide Polymorphisms (SNPs)

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Showing 2 of 2

3D genome mapping identifies subgroup-specific chromosome conformations and tumor-dependency genes in ependymoma.

Okonechnikov K, Camgöz A, Chapman O, Wani S, Park DE, Hübner JM, Chakraborty A, Pagadala M, Bump R, Chandran S, Kraft K, Acuna-Hidalgo R, Reid D, Sikkink K, Mauermann M, Juarez EF, Jenseit A, Robinson JT, Pajtler KW, Milde T, Jäger N, Fiesel P, Morgan L, Sridhar S, Coufal NG, Levy M, Malicki D, Hobbs C, Kingsmore S, Nahas S, Snuderl M, Crawford J, Wechsler-Reya RJ, Davidson TB, Cotter J, Michaiel G, Fleischhack G, Mundlos S, Schmitt A, Carter H, Michealraj KA, Kumar SA, Taylor MD, Rich J, Buchholz F, Mesirov JP, Pfister SM, Ay F, Dixon JR, Kool M, Chavez L

Nat Commun 2023 Apr 21 ;14(1):2300

The landscape of genomic alterations across childhood cancers.

Gröbner SN, Worst BC, Weischenfeldt J, Buchhalter I, Kleinheinz K, Rudneva VA, Johann PD, Balasubramanian GP, Segura-Wang M, Brabetz S, Bender S, Hutter B, Sturm D, Pfaff E, Hübschmann D, Zipprich G, Heinold M, Eils J, Lawerenz C, Erkek S, Lambo S, Waszak S, Blattmann C, Borkhardt A, Kuhlen M, Eggert A, Fulda S, Gessler M, Wegert J, Kappler R, Baumho*r D, Burdach S, Kirschner-Schwabe R, Kontny U, Kulozik AE, Lohmann D, Hettmer S, Eckert C, Bielack S, Nathrath M, Niemeyer C, Richter GH, Schulte J, Siebert R, Westermann F, Molenaar JJ, Vassal G, Witt H, ICGC PedBrain-Seq Project, ICGC MMML-Seq Project, Burkhardt B, Kratz CP, Witt O, van Tilburg CM, Kramm CM, Fleischhack G, Dirksen U, Rutkowski S, Frühwald M, von Hoff K, Wolf S, Klingebiel T, Koscielniak E, Landgraf P, Koster J, Resnick AC, Zhang J, Liu Y, Zhou X, Waanders AJ, Zwijnenburg DA, Raman P, Brors B, Weber UD, Northcott PA, Pajtler KW, Kool M, Piro RM, Korbel JO, Schlesner M, Eils R, Jones DTW, Lichter P, Chavez L, Zapatka M, Pfister SM

Nature 2018 Mar 15 ;555(7696):321-327
Computational Modeling Archives - Sanford Burnham Prebys (2024)
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