Computational Genomics Summer Institute – Apply Today

 

CGSI – extended application deadline

Rolling admissions are starting March 15th.
Registration Fee:

$550 apply by April 1st
$650 apply by April 15th
$750 apply after April 15th
Subsidized housing for CGSI is guaranteed for anyone who applied by April 15th.  Housing for applicants who apply after April 15th will be given on a first come first serve basis subject to availability.

We have filled most of the slots in the 2018 CGSI Long Course, however, there are still a few available slots.
The long program has been a huge success last year and many people were not able to be admitted as they did not apply on time – make sure that this year you are not left behind!
There are also still available spaces in the 2018 CGSI Short Course.
Register now to get the lower rate and subsidized housing.

DATES
SHORT PROGRAM #1: July 16 – 20, 2018
SHORT PROGRAM #2: July 30 – August 3, 2018
LONG PROGRAM: July 11 – August 3, 2018

@ UCLA Campus, Los Angeles
Visit our website to learn more.

The application is open!

Apply now for this upcoming summer’s Short and Long Courses:

STEP #1 APPLY
STEP #2 SEND YOUR CV

 

Watch the best talks in 2018 CGWI

Our first offering of the Computational Genomics Winter Institute was a success. In our feedback survey, we asked the participants to pick three talks they wanted to highlight on our website. We would first like to emphasize that the feedback we got was that all the talks in CGWI were excellent. But we are happy to announce that the ones that received the most votes are the talks of Brian Browning, Casey Greene, Su-In Lee, and John Novembre. We now have links to these videos highlighted on the front page of CGWI for easy access, and links to all of the talks are also available at the CGSI website.

Su-In Lee: “Interpretable Machine Learning for Precision Medicine.”


Casey Greene: “Deep learning: privacy preserving data sharing along with some hints and tips.”


John Novembre: “Computational tools for understanding geographic structure in genetic variation data.”

The 2018 CGSI Organizers

CGSI Co-organizers:
Fereydoun Hormozdiari, UC Davis
David Koslicki, Oregon State University
Kirk Lohmueller, UCLA
Ran Blekhman, University of Minnesota

CGSI Program Co-directors:
Eleazar Eskin, UCLA
Eran Halperin, UCLA
Dima Shlyakhtenko, UCLA IPAM

CGSI Steering Committee
Eleazar Eskin, UCLA
Eran Halperin, UCLA
John Novembre, University of Chicago
Ben Raphael, Princeton University

Involving undergraduates in genomics research to narrow the education-research gap

Serghei Mangul and Lana Martin, together with Eleazar Eskin, recently wrote a paper describing a model for training undergraduates in Bioinformatics. Our paper is available online as a preprint and is under review at a peer-reviewed journal.

The Education-Research Gap in Universities.

While the benefits of undergraduate research experiences (UREs) are recognized for undergraduates, the advantages of UREs for graduate students, post-doctoral scholars, and faculty are not clearly outlined.

Based on our experience mentoring undergraduates in ZarLab, we believe that the analysis of genomic data is particularly well-suited for successful involvement of undergraduates. In computational genomics research, undergraduate trainees who master a particular skill can contribute sufficient work to gain authorship on a peer-reviewed paper.

In our paper, we offer a framework for engaging undergraduates in genomics research while simultaneously improving lab productivity: first, identify particular “low-level” tasks that may take up to a week for an undergraduate to complete. Second, encourage students to “outsource” foundational education needs with workshops, online resources, and review articles. Third, genomics research labs can take advantage of department- and campus-wide undergraduate research and training initiatives.

The proposed strategy can be easily reproduced at other institutions, is pedagogically flexible, and is scalable from smaller to larger laboratory sizes. We hope that genomics researchers will involve undergraduates in more computational tasks that benefit both students and senior laboratory members.

Preprint copies of our manuscript are available for download here: https://peerj.com/preprints/3149/

In tandem with this paper, we created an online catalogue of resources and papers aimed at bridging the research-teaching divide in computational genomics: https://smangul1.github.io/undergraduates-in-genomics/

The full citation of our paper:
Mangul, S., Martin, L. and Eskin, E., 2017. Involving undergraduates in genomics research to narrow the education-research gap. PeerJ Preprints, 5, p.e3149v1.

 

Benefits of UREs to Research Lab and Undergraduates.

Addressing the Digital Divide in Contemporary Biology: Lessons from Teaching UNIX

Serghei Mangul and Lana Martin, together with Alexander Hoffmann, Matteo Pellegrini, and Eleazar Eskin, recently published a paper describing a workshop model for training scientists, who have no computer science background, to use UNIX. Our paper is available online as a preprint and will appear in an upcoming “Scientific Life” section of Trends in Biotechnology.

Scientists who are not trained in computer science face an enormous challenge analyzing high-throughput data. Serghei developed a series of workshops in response to growing demand for life and medical science researchers to analyze their own data using the command line.

Administered by UCLA’s Institute for Quantitative and Computational Biosciences (QCBio), these workshops are designed to help life and medical science researchers use applications that lack a graphical interface. Our paper presents a training model for these workshops—a flexible approach that can be implemented at any institution to teach use of command-line tools when the learner has little to no prior knowledge of UNIX.

QCBio currently offers similar workshops to the UCLA community. In tandem with this publication, we created an online catalogue of resources and papers aimed to provide first-time learners with basic knowledge of command line: https://smangul1.github.io/command-line-teaching/.

We encourage fellow instructors of Bioinformatics, as well as scientists who are new learners of the command line, to read our paper and share their thoughts! Email us at: lana [dot] martin [at] ucla [dot] edu.

 

The full citation of our paper:
Mangul, Serghei, Martin, Lana S., Hoffmann, Alexander, Pellegrini, Matteo, and Eskin, Eleazar. Addressing the Digital Divide in Contemporary Biology: Lessons from Teaching UNIX. Trends in Biotechnology; doi: 10.1016/j.tibtech.2017.06.007.

Advance preprint copies of our paper may be downloaded here: http://www.cell.com/trends/biotechnology/fulltext/S0167-7799(17)30156-7