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» Structured Sparsity in Structured Prediction
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143
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BMCBI
2006
98views more  BMCBI 2006»
15 years 5 months ago
Optimised amino acid specific weighting factors for unbound protein docking
Background: One of the most challenging aspects of protein-protein docking is the inclusion of flexibility into the docking procedure. We developed a postfilter where the grid-rep...
Philipp Heuser, Dietmar Schomburg
CBMS
2006
IEEE
15 years 11 months ago
MS2DB: An Algorithmic Approach to Determine Disulfide Linkage Patterns
Determining the number and location of disulfide bonds within a protein provide valuable insight into the protein’s three-dimensional structure. Purely computational methods tha...
Timothy Lee, Rahul Singh, Ten-Yang Yen, Bruce Mach...
133
Voted
CIBCB
2005
IEEE
15 years 10 months ago
The Homology Kernel: A Biologically Motivated Sequence Embedding into Euclidean Space
— Part of the challenge of modeling protein sequences is their discrete nature. Many of the most powerful statistical and learning techniques are applicable to points in a Euclid...
Eleazar Eskin, Sagi Snir
149
Voted
ISLPED
2004
ACM
108views Hardware» more  ISLPED 2004»
15 years 10 months ago
SEPAS: a highly accurate energy-efficient branch predictor
Designers have invested much effort in developing accurate branch predictors with short learning periods. Such techniques rely on exploiting complex and relatively large structure...
Amirali Baniasadi, Andreas Moshovos
NIPS
2008
15 years 6 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang