Cultivate and expand the bioinformatics capabilities of BU and the greater Boston community.
Bioinformatics Research Partnerships
Bioinformatics analyses of data are becoming a key component of most biological and biomedical research projects. The Bioinformatics Hub strives to put state-of-the-art bioinformatics into widespread practice at BU. To meet these needs, the Hub has established the following objectives:
- Provide biologically-oriented labs access to sustained, project-based bioinformatics expertise
- Assist labs in writing grants that include a bioinformatics component and integrating bioinformatics approaches into their research programs
- Disseminate knowledge about bioinformatics to the BU community and provide training and workshops to equip labs with basic bioinformatics capabilities
- Provide mentorship and hands-on analytical experience to Bioinformatics master’s students
- Connect groups throughout the BU ecosystem who have complementary research interfaces and expertise domains
To accomplish the above objectives, the Hub operates within four functional domains:
The primary role of the Hub is to connect with BU labs that have, or are interested in having, bioinformatics integrated into their research programs. This involves working one-on-one with PIs and their labs to identify which bioinformatics approaches are the most suitable for their particular research area, and performing analysis and communicating results.
The Hub has two tiers of service offerings. The tiers differ primarily in their scope and financial model.
There is no such thing as push-button Bioinformatics. Every biological dataset needs meticulous, individualized attention to reveal its deepest insights. Every dataset is different, and fits into larger scientific goals in ways that are unique and specific to your research program. Bioinformatic analysis often leads to fundamentally novel biological findings and insight, and provides opportunities for new methodological development and avenues of research. Hub.lab projects are designed to foster collaboration and focus on creating new knowledge and understanding as a partner of the labs it works with.
Hub.lab projects are full collaborations, where Hub scientists take an active role in the incorporation and execution of Bioinformatics techniques in your research. These projects are medium- to long-term and typically involve recruiting a dedicated Bioinformatics Masters student to perform the work under the mentorship of the Hub.
Publications and grant proposals frequently grow out of Hub.lab collaborations. Grant proposals should include salary support for Hub scientists to support their participation in the collaboration and limited ancillary costs to maintain Hub operation, e.g. computational infrastructure and storage costs related to the project. Up-front costs of these projects is limited to salary support for the Bioinformatics Masters student hired to perform the work and computational and/or data storage resources required by the project.
While we feel strongly that Hub.lab projects are the best for your science, we recognize that not every project requires a full collaboration. For projects that do not fit the scope of Hub.lab collaborations, the Hub.core service provides traditional bioinformatics core capabilities. Hub.core projects are designed to meet the needs of researchers who have an immediate, concrete analytical need. For discrete, well defined bioinformatics projects, the Hub employs best-practice analytical techniques to produce deliverables that enable the contracting lab to best interpret their data.
Hub.core projects operate on a fee-per-project basis and are designed to require at most ~40 hands-on work hours each. A Hub scientist meet with you to discuss your project individually at no cost to define feasibility and scope, and develop a statement of work that precisely describes the appropriate approach, deliverables, expected timeline, and fees. Project fees may be subsidized using contributions from other sources of sustained support specifically devoted to Hub.core projects, depending on the details of the project.
Please note the Hub.core service offerings are currently in development and very limited
Education and Outreach
The Hub organizes and delivers training opportunities, through classes and workshops, to disseminate and enable bioinformatics capabilities in the BU community. Examples of such events are mRNA-Seq analytical workshops, python and R tutorials aimed at specific types of bioinformatic analyses, and regular classes on practical bioinformatics topics.
Mentorship of Bioinformatics Students
Projects run through the Hub will ideally be performed by Bioinformatics Program master’s students acting as Hub Analysts. Hands-on analysis of real-world biological data, under the guidance of Hub Scientists, will provide master’s students with invaluable skills and training for professional life or research after graduation.
Through communicating directly with people across BU, the Hub serves as a communication conduit by which different groups who have complementary skills and interests may connect. The groups may include academic labs with independent research programs or technical groups that provide analytical expertise and guidance, such as the BU IS&T consulting services or the Biostatistics, Epidemiology, and Data Analytics Center (BEDAC). The goal is to foster collaborations between labs that otherwise might not work together, and help facilitate interactions between groups in identifying how their research priorities can effectively interface.
Bioinformatics Subject Areas
The Hub endeavors to expand the bioinformatics capacity at BU to meet whatever needs exist across biological subdomains. However, at present the Hub’s capability is focused on analysis of genomics data using high-throughput sequence-based technologies. Any research project where the underlying data is microarray or nucleic acid sequencing based is a potential Hub Project. The kinds of analysis that these data types enable include but are not limited to:
- Genome-wide RNA transcription quantification, including mRNA, miRNA, lincRNA, etc
- Differential gene expression and alternative mRNA splicing
- Targeted and genome-wide DNA sequencing
- Phylogenetic analysis
- Microbiome analysis
- Epigenetics, including chromatin immunoprecipitation (ChIP) and DNA methylation
- Single nucleotide polymorphism and indel analysis
- Copy number variation and gene fusion events
- Chromatin interaction and conformation capture, like ChIA-PET and 4C
In time, the Hub will expand analysis capabilities to include other types of biological data, including:
- Proteomics, using mass-spectrometry data
- Volumetric fMRI image data