Biosciences Area

New Computational Biosciences Group Formed

Researchers from Biosciences and the Computational Research Division (CRD) have formed a new integrated Computational Biosciences Group to develop tools for addressing a range of scientific problems that cross organizational lines. Members of the group include (pictured, from left): Héctor García Martin of the Biological Systems and Engineering and the Environmental Genomics and Systems Biology Divisions (BSE/EGSB), acting group lead Kris Bouchard (BSE), Chris Mungall (EGSB), Andrew Tritt of the Computational Research Division(CRD), Oliver Rübel (CRD), and Ben Brown (EGSB). Additional members not pictured are: Aydın Buluç (CRD), Silvia Crivelli (CRD), Hans Johansen (CRD), Talita Perciano (CRD), and Peter Zwart of the Molecular Biophysics and Integrated Bioimaging Division (MBIB).

Read more on the Computing Sciences website.

Building Standards for Neurophysiology Data

Researchers from Berkeley Lab and the Allen Institute for Brain Science will receive $2 million from the National Institutes of Health (NIH) to develop a next-generation data format and software ecosystem for the Neurodata Without Borders: Neurophysiology (NWB:N) project. With funding from the Kavli Foundation, Berkeley Lab scientists Oliver Ruebel and Andrew Tritt in the Computational Research Division and Kristofer Bouchard in the Biological Systems and Engineering Division led the development of the beta version of NWB:N 2.0, and will continue to advance the development of NWB:N as part of the NIH BRAIN Initiative. Berkeley Lab’s leadership in the NWB:N development would have not been possible without the Laboratory Directed Research and Development (LDRD) project BRAINformat: A Data Standardization Framework for Neuroscience Data. Berkeley Lab also hosted a user engagement hackathon earlier this year, bringing together users to help them adopt NWB:N.

Read more from Computing Sciences.

Biosciences Area FY18 LDRD Projects

The projects of 13 Biosciences Area scientists and engineers received funding through the FY18 Laboratory Directed Research and Development (LDRD) program. These projects span a diverse array of topics and approaches including the study of microbiomes in relation to patterns of mutualism, crop productivity, and gut health; synthetic biology for engineering biosurfactant production and energy conversion pathways; and the application of technologies such as machine learning, high-resolution optical microscopy, and single-cell transcriptomics. Together, these efforts account for 18.75 percent of the $20 million allocated. Lab-wide, 74 projects were selected from a field of 215.

Computing Sciences and Biosciences Hold Machine Learning Workshop

The Lab’s Computing Sciences and Biosciences Areas jointly held a week-long workshop focused on machine learning in data science, the goal of which was to build bridges through a common foundation in statistical computing. Thirty attendees from Biosciences, Computing Sciences, and Lab IT received hands-on training provided by Data Incubator before engaging in a “hackathon” to apply the techniques to relevant science problems and data sets.

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