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James J. Collins

Researcher at Massachusetts Institute of Technology

Publications -  700
Citations -  105255

James J. Collins is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Synthetic biology & Population. The author has an hindex of 151, co-authored 669 publications receiving 89476 citations. Previous affiliations of James J. Collins include Baylor College of Medicine & University at Albany, SUNY.

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Humanized microbiota mice as a model of recurrent Clostridium difficile disease

James J. Collins, +4 more
- 20 Aug 2015 - 
TL;DR: The identification and testing of human-derived microbial communities within a humanized microbiota mouse model may enable a higher rate of successful transfer of bacteria-based treatments from the lab to human patients due to the microbes involved initiating from, and being adapted to, the human GI tract.
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Pinned polymer model of posture control.

Carson C. Chow, +1 more
- 01 Jul 1995 - 
TL;DR: A phenomenological model of human posture control is posited that accurately reproduces the two-point correlation functions of experimental posture data and makes predictions for the response function of the postural control system.
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Antibiotic efficacy — context matters

Jason H. Yang, +5 more
- 01 Oct 2017 - 
TL;DR: Recent studies on antibiotic efficacy are reviewed and insights gained on the involvement of cellular respiration, redox stress and altered metabolism in antibiotic lethality are highlighted.

Designing microbial consortia with defined social interactions

Wentao Kong, +5 more
TL;DR: It is shown that models derived from two-strain consortia can be used to design three- and four-strains ecosystems with predictable behaviors and further extended to provide insights into community dynamics in space.
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Deep learning identifies synergistic drug combinations for treating COVID-19.

Wengong Jin, +7 more
- 28 Sep 2021 - 
TL;DR: In this article, a neural network architecture was proposed to jointly learn drug-target interaction and drug-drug synergy for new diseases with limited combination data, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).