Our programmers and software engineers are expected to contribute most of the code that goes into our production ready webservers and analytical pipelines. These professionals are expected to maintain high standards for code documentation, clarity, efficiency and maintainability. In addition to maintaining these standards in their own code, these members of the lab set high expectations for other lab members and share their expertise to improve the code that all members of the lab are writing. For the machine learning aspects of our work, we currently use a technology stack consisting of C/C++ (limited and decreasing), Python + numpy/scipy/scikit-learn/theano, and R with assorted packages. For the web development side of the lab, we currently use a technology stack of Postgres, Python (Django), and JavaScript (Angular.js and d3).

RENÉ Zelaya


René graduated in 2012 with a B.A. in Engineering Sciences from Dartmouth College. He started working as a programmer in the Integrative Genomics Lab during the spring of 2013. His primary mission is to put our research advances into the hands of biologists. He works with users to understand how we can make their lives easier through accessible computation. He translates these conversations, in the context of our machine learning advances, into functionality embedded inwebservers such as GIANT and Tribe that address key biological challenges. René also manages the code review process in the lab, which keeps our group thinking about both design and documentation principles.


Matt Huyck


Matt has been translating questions posed by biologists and businesses into software that computers can contemplate for over 20 years. He earned his Bachelor’s Degree in Applied and Engineering Physics at Cornell University at the same time the Human Genome Project was getting underway. He has a broad and deep background in using and developing complex computer software. As a Project Manager for diverse consulting clients, he developed a specialty for systems integration. He also has worked as a programmer and data analyst in an array of academic settings, including the MIRAGE Alzheimer Disease project at Boston University Medical Center and as a member of the Harvard Computational Biology Initiative, where he played an integral role in creating innovative visual displays of gene networks that became Autworks. His research interests include visualization of information and human-computer interaction as applied to complex data sets. At the Greene Lab, he enjoys the challenge of making novel research methods available and useful to a broader audience of biologists. [E-mail]


Dongbo Hu


Dongbo used to be a chemist but was eventually attracted into computer science because of its elegance. Before taking this position, he worked in the Neurology Department of Penn's hospital, Penn's Genetics Department and at a local financial firm. In the Greene lab, he is working on the ADAGE web server.