Everyday challenges are being executed for progressive innovation and growth. From DNA sequencing to myeloma progression prediction, we have the talent to help you execute faster, stronger, and with precision.
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LIFE SCIENCES: DATA SCIENCE IN THE ERA OF PRECISION MEDICINE
What's Your Challenge?
The Harvard Tumor Hunt is one of many projects resulting from a co-partnership between Harvard and Topcoder. From computational biology to precision medicine, Harvard and Topcoder have created an atmosphere of continuous progress and success in the fields of medicine, biology, and technology. Our partnership with The Laboratory for Innovation Science at Harvard (LISH) has been the catalyst for some of crowdsourcing’s most sophisticated and far-reaching successes.
Topcoder & Harvard: Continued Success
HARVARD AND TOPCODER SEEK TO DISRUPT CANCER DELINEATION, IMPACTING MILLIONS
The Topcoder community tackled complex data analytic challenges before the term crowdsourcing was coined by Jeff Howe in 2006. During those years, our community of data and computer scientists handled projects aimed at increasing the quality of people’s lives, detecting risk in big business, and exploring the vast wonders of space. All of these projects share one common thread; they make use of our deep well of motivated and intelligent data scientists to tackle real, complex problems.
Lung cancer claims over 150,000 people’s lives every single year. Recently, Topcoder joined forces with Harvard to tackle one of the most ambitious healthcare initiatives ever undertaken in the crowdsourcing world… Creating and testing automatic delineation algorithms to help improve treatments of cancerous tumors in patients’ lungs.
This project was so successful that the results were recently validated by JAMA, the Journal of the American Medical Association and we invite you to download the report to view the results for yourself.
DNA SEQUENCING 1 (DNAS1)
In the first contest of the DNA series, we looked for an algorithm that aligns multiple DNA sequences to a reference DNA for a simpler case, when there are only minor differences between the reference DNA and the DNA the sequences are originated from. The task is to align the sequences fast, align them right, and test the alignment position for possible redundancies.
Total Prize Purse: $20,000
CONNECTIVITY MAP 1 (CMAP1)
CMAP was a collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive, small molecules, and simple pattern-matching algorithms. When these elements are brought together, the results enable the discovery of functional connections between drugs, genes, and diseases through the transitory feature of common gene-expression changes.
For this contest, the goal was to maximize the accuracy of the inferred gene expression values, while minimizing the number of the measured gene expressions. The results of this contest will further expand research horizons for computational biologists and scientists who seek to find drugs that cure diseases.
Total Prize Purse: $20,000
MYELOMA PROGRESSION PREDICTOR
Helped predict cancer by creating advanced algorithms using real genetic data. MMRF, Harvard, and Topcoder needed algorithmic solutions to this hugely important challenge.
Total Prize Purse: $20,000
