Arthur P Goldberg, PhD Email Arthur Goldberg
- ASSOCIATE PROFESSOR | Genetics and Genomic Sciences
Professor Goldberg has a degree in Astrophysics from Harvard and a PhD in Computer Science from UCLA. He entered bioinformatics after a distinguished career researching distributed software at IBM Research and network protocol performance at NYU’s Courant Institute of Mathematical Sciences.
The aim of his current work is to help researchers achieve human whole-cell (WC) models that enable physicians to personalize medicine. To this end, he develops algorithms and software for building, simulating, and analyzing WC models. WC models are computational models that predict how genotype influences phenotype by accounting for every gene function in a cell. His methods systemize and accelerate WC modeling and enable scientists to efficiently build and simulate WC models. In particular, he is inventing methods that enable researchers to create models of human cells that represent all annotated human genes and can guide medicine by screening drugs in silico.
Previously, as a Research Scientist in Bioinformatics in the Plant Systems Biology Laboratory at NYU he co-designed and co-implemented the Virtual Plant System, which provides tools to conveniently visualize and analyze gene expression and network data about the model plant Arabidopsis and crops.
At Sloan-Kettering, Dr. Goldberg co-designed and co-developed the cBioPortal for Cancer Genomics, a website that enables researchers to visualize and analyze multiple types of cancer genetic data. The cBioPortal stores all of the NCI’s reduced Cancer Genome Atlas (TCGA) data, along with data from multiple other studies.
Dr. Goldberg is an Associate Professor for the Department of Genetics and Genomic Sciences and the Icahn Institute for Data Science and Genomic Technology. As a member of the Seaver Autism Center in the Icahn School of Medicine at Mount Sinai, Prof. Goldberg studied the genetic causes of autism. He was the founding Director of the Bioinformatic Hub for the NIMH-funded Autism Sequencing Consortium (ASC). The Hub stores published and unpublished sequence data and called variants from autism studies by ASC members and provides secure, shared data access and cluster computing to ASC members. Dr. Goldberg built a three person bioinformatics team for the Seaver Center.
Autism, Bacterial Genetics, Bioinformatics, Biomedical Informatics, Biophysics, Cancer Genetics, Cell Biology, Computational Biology, Computer Simulation, Genetics, Genomics, Human Genetics and Genetic Disorders, Mathematical Modeling of Biomedical Systems, Mathematical and Computational Biology, Systems Biology
BA, Harvard College
PhD, University of California, Los Angeles
Gene discovery in complex heritable diseases such as autism
Prof. Goldberg and his collaborators work on identifying risk genes in Autism Spectrum Disorder (ASD).
Work with Christopher Poultney, Joseph Buxbaum and others found that small (1-30 kilobase) copy number variant deletions are enriched in ASD cases versus matched controls. Genes disrupted by these variants are overrepresented in the autophagy pathway, suggesting that improper pruning of neuronal interconnections during development may contribute to autism. This work won a top 10 paper of the year award from SFARI in 2013.
Work with many collaborators including Silvia De Rubeis, Xin He, Christopher Poultney, Menachem Fromer, Kathryn Roeder, Bernie Devlin, Mark Daly, Joseph Buxbaum, and other members of the ASC focused on discovering new autism risk genes on the autosomes. Employing a powerful new statistical model called Transmission and De novo Analysis (TADA) [He et. al., 2013] we implicate 22 autosomal genes at an FDR
Software tools for studying heritable diseases
Professor Goldberg creates programs that organize and analyze genetic data. Recently developed tools include
- A program that identifies the transmission status of variants on the sex chromosomes in males and females.
- A pipeline that inputs variant call (vcf) and pedigree (PED) files and filters outlier subjects and common variants to produce input for the Transmission And De novo Analysis (TADA) gene risk statistical analysis. The analysis tallies transmitted, de novo, and case-control variants, while properly handling the sex chromosomes and integrating dependency analysis to perform well with over 10,000 subjects.
- A database that stores and analyzes identifier aliases and pedigree relationships in large samples of genetic subjects.
Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device and biotechnology companies to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their relationships with such companies.
Dr. Goldberg has not yet completed reporting of Industry relationships.
Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.
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