Draft:David K. Gifford
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David Kenneth Gifford | |
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Born | October 22, 1954 |
Occupation | Computer science professor |
Academic background | |
Alma mater | Stanford University |
Thesis | Information storage in a decentralized computer system (1981) |
Doctoral advisor | Susan Owicki |
Academic work | |
Discipline | Computer scientist |
Doctoral students | Ziv Bar-Joseph |
Notable works | Design Concepts in Programming Languages |
David K. Gifford (born 22 October 1954) is a computer science professor at the Massachusetts Institute of Technology (MIT) in the area of computational biology. As a Principal Investigator in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), he leads research in developing interpretable computational models for drug development, immunology, genomics, and human therapeutics.
Gifford received his BS from MIT in 1976, and his PhD from Stanford University in 1981. He joined the MIT faculty in 1982, where he is Professor of Computer Science and Engineering and Professor of Biological Engineering.
His group develops combined computational and experimental approaches to the discovery of novel biology and human therapeutics. Some of his work involves looking at non-coding genes in the genome known as non-functional DNA. He has collaborated on techniques for searching long stretches of the genome to identify new regions that appear to play a crucial role in gene regulation.[1]
His group has also worked to develop drugs for specific health conditions. His team's protocols for the direct programming of stem cells into motor neurons has shown promise as a regenerative medicine for motor neuron diseases.[2]
More recently Gifford's group has used machine learning methods to help scientists use CRISPR, specifically with predicting DNA repair outcomes in the form of insertions or deletions.[3] The tool can be used to predict genetic diseases that can be cured by the direct application of CRISPR. He has also helped create pan-variant COVID-19 vaccines that work on a wider swath of diverse populations[4] and have been shown in mice to be able to protect against a highly pathogenic variant of COVID-19.[5]
In 2011 Gifford was named a fellow of the Association for Computing Machinery[6] for "contributions to distributed systems, e-commerce and content distribution".
Gifford has also founded multiple companies, including e-commerce site Open Market and the biotech startup Think Therapeutics. His company SightPath was bought by Cisco in 2002 for $800 million.[7]
References
[edit]- ^ "Mapping regulatory elements". mit.edu. 27 January 2016.
- ^ Mazzoni, Esteban O.; Mahony, Shaun; Closser, Michael; Morrison, Carolyn A.; Nedelec, Stephane; Williams, Damian J.; An, Disi; Gifford, David K.; Wichterle, Hynek (2013). "Synergistic binding of transcription factors to cell-specific enhancers programs motor neuron identity". Nature Neuroscience. 16 (9): 1219–1227. doi:10.1038/nn.3467. PMC 3820498. PMID 23872598.
- ^ Shen, Max W.; Arbab, Mandana; Hsu, Jonathan Y.; Worstell, Daniel; Culbertson, Sannie J.; Krabbe, Olga; Cassa, Christopher A.; Liu, David R.; Gifford, David K.; Sherwood, Richard I. (2018). "Predictable and precise template-free CRISPR editing of pathogenic variants". Nature. 563 (7733): 646–651. Bibcode:2018Natur.563..646S. doi:10.1038/s41586-018-0686-x. PMC 6517069. PMID 30405244.
- ^ Liu, Ge; Dimitrakakis, Alexander; Carter, Brandon; Gifford, David (6 October 2021). "Maximum n-times Coverage for Vaccine Design". openreview.net. arXiv:2101.10902.
- ^ Carter, Brandon; Huang, Pinghan; Liu, Ge; Liang, Yuejin; Lin, Paulo J.C.; Peng, Bi-Hung; McKay, Lindsay; Dimitrakakis, Alexander; Hsu, Jason; Tat, Vivian; Saenkham-Huntsinger, Panatda; Chen, Jinjin; Kaseke, Clarety; Gaiha, Gaurav D.; Xu, Qiaobing; Griffiths, Anthony; Tam, Ying K.; Tseng, Chien-Te K.; Gifford, David K. (2022). "A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta". biorxiv.org. doi:10.1101/2022.09.23.509206.
- ^ "David K Gifford". acm.org.
- ^ "Cisco to acquire SightPath for $800 million". cnet.com.