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Case study: gget’s new Open Target module

The Open Targets Blog

  “Sam has an exceptional talent in software engineering, and his contributions reflect a deep understanding of both the technical and biological aspects required for bioinformatics tool development,” says Laura Luebbert, now a postdoctoral fellow in the Sabeti lab at the Broad Institute of MIT and Harvard and Harvard University.

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From siloed data to breakthroughs: multimodal AI in drug discovery

Drug Target Review

His leadership has driven international commercial success in areas including image analysis, data management, bioinformatics, advanced clinical trial data analysis leveraging machine learning and federated learning. Nature Medicine, 28, 1656–1661 (2022) [link] Nature, 596, 590-596 (2021) [link] Liu R, Rizzo S, Waliany S, et al.

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Unlocking the potential of natural products in drug discovery

Drug Target Review

In a 2022 review, the authors posited that natural product drugs, or those closely mimicking natural products, may possess conserved recognition elements and associated properties, functioning in evolutionarily optimized ways. References Newman DJ, Cragg GM. Journal of Natural Products. 2020;83(3):770–803. doi:10.1021/acs.jnatprod.9b01285

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Three reflections from David Hulcoop's first year as Executive Director

The Open Targets Blog

Building and Sustaining I have huge admiration for the incredible teams at EMBL’s European Bioinformatics Institute and beyond who build and sustain knowledge resources for the community. I am really excited about bringing this to life with the team and where it will take us.

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Molecular map reveals insights into the genetic drivers of chronic lymphocytic leukemia

Broad Institute

By Tracy Hampton August 4, 2022 Credit: National Institutes of Allergy and Infectious Diseases, National Institutes of Health Colorized scanning electron micrograph of a B cell lymphocyte from a human donor. "Our Online August 4, 2022. Paper(s) cited Knisbacher BA, Lin Z, Hahn CK, Nadeu F, Duran-Ferrer M, et al. Nature Genetics.

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AI in Drug Discovery - A Highly Opinionated Literature Review (Part II)

Practical Cheminformatics

In 2022, several papers , including one of ours , showed the promise of active learning approaches in drug discovery. In our 2022 paper , we evaluated 5 different ML models and saw minimal differences in performance. The ML model can predict the remaining molecules' free energies and prioritize the next set of free energy calculations.

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A scientist devotes her career to tackling inequity in genomics

Broad Institute

Alicia Martin and attendees of the KEMRI-Wellcome Trust/GINGER Bioinformatics training in Kilifi, Kenya in September 2018. The program collaborates with academic and research institutions and has been training fellows in bioinformatics, statistics, clinical science, and genetics for the last six years.