David K. Gifford
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David Gifford 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. The following year he joined the faculty at MIT, 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 that researchers previously assumed to be “junk DNA.” He has collaborated with Harvard researchers on techniques for searching long stretches of the genome to identify new regions that appear to play important roles 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 COVID-19 vaccines that work on a wider swath of populations[4] and have been shown in mice to be able to protect against a highly pathogenic variant of COVID-19[5]
References[edit]
- ↑ Rajagopal, Nisha; Srinivasan, Sharanya; Kooshesh, Kameron; Guo, Yuchun; Edwards, Matthew D.; Banerjee, Budhaditya; Syed, Tahin; Emons, Bart J. M.; Gifford, David K.; Sherwood, Richard I. (February 2016). "High-throughput mapping of regulatory DNA". Nature Biotechnology. 34 (2): 167–174. doi:10.1038/nbt.3468. ISSN 1546-1696. PMC 5108523. PMID 26807528.
- ↑ Mazzoni, Esteban O.; Mahony, Shaun; Closser, Michael; Morrison, Carolyn A.; Nedelec, Stephane; Williams, Damian J.; An, Disi; Gifford, David K.; Wichterle, Hynek (September 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. ISSN 1546-1726.
- ↑ 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. (November 2018). "Predictable and precise template-free CRISPR editing of pathogenic variants". Nature. 563 (7733): 646–651. doi:10.1038/s41586-018-0686-x. ISSN 1476-4687.
- ↑ Liu, Ge; Dimitrakakis, Alexander; Carter, Brandon; Gifford, David (2022-01-28). "Maximum n-times Coverage for Vaccine Design".
- ↑ 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 (2022-11-11). "A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta": 2022.09.23.509206. doi:10.1101/2022.09.23.509206v3.
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