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Chris Sander

Researcher at Harvard University

Publications -  730
Citations -  273726

Chris Sander is an academic researcher from Harvard University. The author has contributed to research in topics: Large Hadron Collider & Protein structure. The author has an hindex of 178, co-authored 713 publications receiving 233287 citations. Previous affiliations of Chris Sander include Purdue University & University of Leeds.

Papers
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Proceedings Article

3-D lookup: fast protein structure database searches at 90% reliability.

Liisa Holm, +1 more
TL;DR: In this article, a top-down approach is proposed to identify 3D similarities between a query structure and the database of known protein structures. But the problem of detecting three-dimensional similarities is NP-complete.
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Using Biological Pathway Data with Paxtools

Emek Demir, +8 more
- 19 Sep 2013 - 
TL;DR: Paxtools is a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language that allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information.
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A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment

Morad Aaboud, +2902 more
- 06 Feb 2019 - 
TL;DR: In this article, the authors describe a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics, where events are classified according to their final state into many eve...
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From bytes to bedside: data integration and computational biology for translational cancer research.

Jomol Mathew, +12 more
- 23 Feb 2007 - 
TL;DR: Key challenges are standardization of data capture and communication, organization of easily accessible repositories, and algorithms for integrated analysis based on heterogeneous sources of information.
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Computer-guided design of optimal microbial consortia for immune system modulation.

Richard R. Stein, +15 more
- 17 Apr 2018 - 
TL;DR: A novel workflow to select optimal immune-inducing consortia from microbiome compositicon and immune effectors measurements and argues that computational indexes, such as the TrIS, are valuable tools for the systematic selection of immune-modulating bacteriotherapeutics.