Community Research Education and Engagement for Data Science

The Community Research Education and Engagement for Data Science (CREEDS) will advance research education by providing (a) an intensive, practical spring school in RNA sequencing for postdocs and early career faculty, (b) an intensive, practical summer school experience in computational genomics for graduate students, and (c) DREAM Challenges and problem solving to tackle real-life biomedical questions for graduate students, (d) an online collaboration environment, and (e) active recruitment and retention of underrepresented groups. This program is funded through the NIH Big Data to Knowledge (BD2K), award #1R25EB020393.

The Mission

  • To provide biomedical researchers with the practical skills and insight needed to harness the power and advance the promise of big data science to accelerate scientific discovery
  • To develop an online social environment which will facilitate the exchange of big data ideas and other approaches and techniques between novices and experts
  • To enhance the diversity of the biomedical big data workforce through targeted recruitment and retention of disadvantaged and underrepresented student populations

2017 Spring Curriculum
2017 Spring Flyer

Program Participants

The intended participants are postdoctoral fellows and early career faculty in computer science or biology. The spring school will provide training on basic computational skills and genomic information. This program strives to enhance the diversity of the biomedical big data workforce through recruitment of individuals from diverse racial, ethnic, cultural, and socioeconomic backgrounds. We encourage applications from economically underrepresented groups.

There is a competitive selection process for applicants; and for those selected there is no fee to attend the course. In addition, housing will be provided at no cost for accepted applicants from outside the NY metro area, and travel stipends are also available.

Applying to the Spring School for RNA-seq Sequence Analysis

For the May 15th – May 19th, 2017 session, enrollment applications are due by February 10th, 2017. Applicants for all activities must be U.S. citizens or permanent residents and will need to submit the following materials:

  • Resume
  • A Letter of Recommendation. Postdoctoral Applicants: The Recommender must be your advisor. Other Applicants (non-Postdoctoral): The Recommender should be a faculty member who knows you well enough to determine if you would benefit from the training
  • A 300-word description of what you hope to learn and what you plan to do with the knowledge gained from the summer school program
  • A PDF copy of your transcript. Icahn School of Medicine requires international applicants to have their foreign transcripts translated into English by a certified foreign credential translation service (ex. WES, ECE, FIS). Applicants should request that these translated documents be sent directly to the Icahn School of Medicine at Mount Sinai along with official original transcripts from their institution.

Apply Now

Applicants are unable to apply to both the Spring and Summer school using the same login account within the application system.

Applicants must create a second login account if applying to the second program.

The Mission

  • To provide biomedical researchers with the practical skills and insight needed to harness the power and advance the promise of big data science to accelerate scientific discovery
  • To develop an online social environment to facilitate the exchange of big data ideas, approaches and techniques between novices and experts
  • To enhance the diversity of the biomedical big data workforce through targeted recruitment and retention of disadvantaged and underrepresented student populations

2017 Summer Curriculum
2017 Summer Flyer

Program Participants

The intended participants are first- and second-year graduate students in computer science or biology. The summer school will provide training on basic computational skills and genomic information. This program strives to enhance the diversity of the biomedical big data workforce through recruitment of individuals from diverse racial, ethnic, cultural, and socioeconomic backgrounds. We encourage applications from economically underrepresented groups.

There is a competitive selection process for applicants; and for those selected there is no fee to attend the course. In addition, housing will be provided at no cost for accepted applicants from outside the NY metro area, and travel stipends are also available.

Applying to Summer School for Computational Genomics

For the June 12th - June 23rd, 2017 session, enrollment applications are due by February 10th, 2017. Applicants for all activities must be U.S. citizens or permanent residents and will need to submit the following materials:

  • Resume
  • A Letter of Recommendation. Postdoctoral Applicants: The Recommender must be your advisor. Other Applicants (non-Postdoctoral): The Recommender should be a faculty member who knows you well enough to determine if you would benefit from the training
  • A 300-word description of what you hope to learn and what you plan to do with the knowledge gained from the summer school program
  • A PDF copy of your transcript. Icahn School of Medicine requires international applicants to have their foreign transcripts translated into English by a certified foreign credential translation service (ex. WES, ECE, FIS). Applicants should request that these translated documents be sent directly to the Icahn School of Medicine at Mount Sinai along with official original transcripts from their institution.

Apply Now

Applicants are unable to apply to both the Spring and Summer school using the same login account within the application system.

Applicants must create a second login account if applying to the second program.

Instructors

Applications are due April 1, 2017.
The Academy will begin mid-May 2017. 

The Mission

The speed of advancement in data-rich biomedical sciences is limited in part by the lack of awareness and expertise in big data sets and tools, the absence of approaches that productively intersect disparate domains, and the underrepresentation of diverse groups in the workforce. The mission of the DREAM Challenges Academy is to provide early-career biomedical researchers with the practical skills and insight needed to harness the power and advance the promise of big data science to accelerate scientific discovery.

The Target DREAM Challenges Academy

Despite millions of cases of acute respiratory illnesses documented on an annual basis, many humans exposed to viruses are resilient to these pathogens. The Resilience to Infectious Diseases DREAM Challenges Academy is designed to assess the capabilities of developing early-stage predictors of viral resilience based on peripheral blood expression patterns of host immune response. Participants will be challenged to build predictors from time-series expression data that can distinguish people who do not get sick following exposure to flu and other respiratory viruses, as measured by resilience to contracting the virus and resilience to symptomatic manifestations of illness.

Skill Development

Team problem-solving, big data techniques to solve the DREAM Challenges Academy, machine learning, data exploration/statistics (PCA, clustering), network inference, modeling the biology of the problem, programming in High-Performance Computing environments.

You will work with peers as well as gain expertise through lectures (two 2-hour lectures per week for a month).

DREAM Challenge Academy Mentors

Pablo Meyer, PhD, Research Staff Member, IBM Research

Gaurav Pandey, PhD, Assistant Professor, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai

Gustavo Stolovitzky, PhD, Adjunct Professor, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai; Program Director, Translational Systems Biology and Nanobiotechnology, IBM Research 

DREAM Challenges Academy Curriculum

Cost: There is no fee to participate in the DREAM Challenges Academy.

Eligibility: Intended participants for the DREAM Challenges Academy are senior undergraduate and graduate students, and post-doctoral fellows. Some knowledge of biology and/or programming is preferred. Applicants must be U.S. citizens or permanent residents.

For more information on the DREAM Challenges Academy community, please visit dreamchallenges.org.

This program strives to enhance the diversity of the biomedical big data workforce through recruitment of individuals from diverse racial, ethnic, cultural, and socioeconomic backgrounds.

Course Directors

Advisory Board

  • C. Titus Brown, PhD (UC-Davis)
  • Ilkay Altintas, PhD (UCSD)
  • Terry Krulwich, PhD (ISMMS)
  • Erin Flaherty, PhD (ISMMS)