Computational Biology Algorithms

LISH is using crowdsourcing techniques to break data bottlenecks in computational biology and genomic sequencing problems by broadening the field of solvers. Through prize-based contests, we look to advance data mining correlations in big data, establish an infrastructure functionality to support research data collaboration, and conceptualize methods for data model interpretation. Our partners include Harvard Medical School, the Broad Institute, Scripps Research Institute, and cancer foundations. Together we look to explore novel ideas and solutions that foster rapid prototyping and facilitate faster research.

Mechanisms of Action (MoA) Prediction Contest

The Connectivity Map, a project within the Broad Institute of MIT and Harvard, LISH and the NIH Common Funds Library of Integrated Network-Based Cellular Signatures (LINCS), launched the Mechanisms of Action Prediction Contest in August 2020.... Read more about Mechanisms of Action (MoA) Prediction Contest

Single Cell Trajectory Contest

The Pinello Lab at Massachusetts General Hospital, LISH, and 25+ other single cell labs across the world collaborated to execute the Single Cell Trajectory contest. Single cell trajectory inference methods are essential tools in the analysis of cellular dynamic processes. In the field, there are over 60 methods used for prediction... Read more about Single Cell Trajectory Contest

Antibody Clustering Challenge

The goal of this 2015 challenge, conducted in collaboration with the Scripps Research Institute on Topcoder, was to optimize and speed up an existing algorithm for clustering antibody sequences (see the problem statement). Clustering these sequences allows researchers to understand... Read more about Antibody Clustering Challenge

Antibody Sequencing Algorithm Challenge

The goal of this 2013 precision medicine challenge, conducted with Harvard Medical School on Topcoder, was to find a faster, more accurate solution to calculate the edit distance between a query DNA string and the original DNA string. Prior to the contest, the best-known solution,... Read more about Antibody Sequencing Algorithm Challenge

DNA Sequencing Challenge

In collaboration with the Broad Institute, the goal of this 2016 precision medicine contest was to find an algorithm that aligned multiple DNA sequences to a reference DNA for a simpler case. The reference DNA and the DNA from which the sequences originated had only minor differences. The task was to align these sequences fast and accurately,... Read more about DNA Sequencing Challenge

Connectivity Map 1

The Broad Institute's Connectivity Map is a collection of genome-wide, transcriptional expression data from cultured human cells. The data is used to find the functional connections between drugs, genes, and diseases through the transitory feature of common... Read more about Connectivity Map 1

Connectivity Map 2

The Broad Institute's Connectivity Map is a collection of genome-wide, transcriptional expression data from cultured human cells. The data is used to find the functional connections between drugs, genes, and diseases through the transitory feature of common... Read more about Connectivity Map 2

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Computational Biology Algorithms

Mechanisms of Action (MoA) Prediction Contest

Single Cell Trajectory Contest

Antibody Clustering Challenge

Antibody Sequencing Algorithm Challenge

DNA Sequencing Challenge

Connectivity Map 1

Connectivity Map 2

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