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Bioinformatics and Computational Biology: Home


Springer has released 65 Machine Learning and Data books for free. 

See a full list in this blog post here


Two new grant writing books, written by experienced grant writers. These two versions are specifically targeted for NIH and NSF, respectively, and provide in-depth insiders' tips for writing grants for the desired funding agency.

The grant application writer’s workbook : National Institutes of Health version (January 2018 edition.)
Robertson, J., Russell, S., & Morrison, D. (2018). Buellton, CA: Grant Writers’ Seminars and Workshops, LLC.


The grant application writer’s workbook. National Science Foundation, FastLane version (01/2017 edition.)
Russell, S., & Morrison, D. (2017). Buellton, CA: Grant Writers’ Seminars and Workshops, LLC.



A machine readable COVID-19 Open Research Dataset is released by Allen Institute for AI, and a Call to Action and Research Challenge to the AI experts is issued by the White House to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions.

Others organizations including WHO and NIH, also curated up-to-date COVID-19 publications datasets. See my guide here for details. 

Semantic Scholar

Image result for semantic scholar logo

Semantic Scholar
A free research and discovery tool that provides access to over 170 million research publications in all scientific domains. Powered by AI, Semantic Scholar enables you to find relevant information more quickly, helps you stay-up-to-date, and manage your papers. Developed by the non-profit research institute, Allen Institute for Artificial Intelligence, Semantic Scholar is a state of the art tool created by scholars for scholars.

Collaborative Writing in LaTeX




Overleaf: A web-based collaborative writing tool for LaTeX. It allows real-time collaborations in your browser, and provides many templates for specific journals or conferences. With a CMU license, you have 20GB storage, and unlimited number of collaborators. 

Platform for Computational Reproducibility


Code Ocean is a cloud-based computational reproducibility platform that provides researchers and developers an easy way to share, discover and run code published in academic journals and conferences.

For the first time, researchers, engineers, developers and scientists can upload code and data in any open source programming language and link working code in a computational environment with the associated article for free. A Digital Object Identifier (DOI) will be assigned to the algorithm, providing correct attribution and a connection to the published research.

The platform provides open access to the published software code and data to view and download for everyone for free. But the real treat is that users can execute all published code without installing anything on their personal computer. Everything runs in the cloud on CPUs or GPUs according to the user needs. We make it easy to change parameters, modify the code, upload data, run it again, and see how the results change.


Supercomputing Resources

Bridges: A new approach to supercomputing

Through the Pittsburgh Supercomputing Center, CMU researchers have free access to Bridges, an NSF-funded supercomputer designed to enable a wide variety of research communities, including those that may not have a lot of experience with programming and do not typically use supercomputers.

Bridges can be used for analysis in a variety of fields including genomics, neuroscience, and machine learning and can be used with familiar, widely-used software such as R, MATLAB, and Python.

​To find out if Bridges is right for you or to request access, follow the "Apply Now" link at Pittsburgh Research Computing Initiative or email



Questions? Suggestions?

Email me, or schedule a one-on-one research consultation.

Huajin Wang's picture
Huajin Wang
Mellon Institute Library
4th Floor Mellon Institute