Campus alert status is yellow: For the latest campus alert status, news and resources, visit umassmed.edu/coronavirus

Search Close Search
Search Close Search
  • Female Scientist
  • Puzzle
  • Pipette
  • Server Datacenter
  • Speaker
Page Menu

DolphinSuite | Training | Support

The Bioinformatics Core facility (BioCore) created DolphinSuite, a platform to support the analysis of high throughput data. DolphinSuite supports the full research cycle by allowing clients to track samples from sample collection to data processing (sequencing, proteomics, metabolomics) and finally to interactive analysis using an intuitive web interface. DolphinSuite is built to ensure secure access to the processed data using 3rd party applications for tailor-made analysis and data sharing. The core facility provides DolphinSuite training and assists laboratories and other core facilities in installing maintaining and, when required, developing new functionality.

Customization | Consulting

The core will also engage in strategic consulting to provide data analysis services to assist researchers in analyzing data generated from sequencing studies (RNA-Seq, scRNA-Seq, ChIP-Seq, ATAC-Seq, small RNA-Seq, exome and whole genome sequencing, Methyl-Seq), and microarray studies (gene chips, tiling arrays, SNP arrays).

WHO WE ARE…

BioCore is a team that develops tools for the researchers in UMCMS and their collaborators.

In the last years sequencing has become the readout of choice for many assays ranging from transcriptional annotation and quantification (RNA-Seq), protein-nucleic acid interactions (ChIP and CLIP sequencing), genotyping through exome or whole genome sequencing. While allowing for unbiased, genome-wide data generation, the analysis of this data requires significant computational expertise and is often not carried out by those who generate it.

OUR MISSION…

The Bioinformatics Core mission is two-fold:

1) To evaluate, select, and implement when needed the best of breed computational solutions for the analysis of biological data.  

2) To allow those who generate the data to be able to analyze it using state of the art methods by reducing the computational expertise required to apply these methods.