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The structural basis of peptide-protein binding strategies.
Peptide-protein interactions are very prevalent, mediating key processes such as signal transduction and protein trafficking. How can peptides overcome the entropic cost involved in switching from anExpand
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Analysis of the reputation system and user contributions on a question answering website: StackOverflow
Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide aExpand
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Bugram: Bug detection with n-gram language models
To improve software reliability, many rule-based techniques have been proposed to infer programming rules and detect violations of these rules as bugs. These rule-based approaches often rely on theExpand
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Can self‐inhibitory peptides be derived from the interfaces of globular protein–protein interactions?
In this study, we assess on a large scale the possibility of deriving self‐inhibitory peptides from protein domains with globular architectures. Such inhibitory peptides would inhibit interactions ofExpand
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Natural Language Models for Predicting Programming Comments
Statistical language models have successfully been used to describe and analyze natural language documents. Recent work applying language models to programming languages is focused on the task ofExpand
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KB-LDA: Jointly Learning a Knowledge Base of Hierarchy, Relations, and Facts
Many existing knowledge bases (KBs), including Freebase, Yago, and NELL, rely on a fixed ontology, given as an input to the system, which defines the data to be cataloged in the KB, i.e., a hierarchyExpand
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Detection of peptide‐binding sites on protein surfaces: The first step toward the modeling and targeting of peptide‐mediated interactions
Peptide‐mediated interactions, in which a short linear motif binds to a globular domain, play major roles in cellular regulation. An accurate structural model of this type of interaction is anExpand
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Graph Agreement Models for Semi-Supervised Learning
Graph-based algorithms are among the most successful paradigms for solving semi-supervised learning tasks. Recent work on graph convolutional networks and neural graph learning methods hasExpand
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Bootstrapping Biomedical Ontologies for Scientific Text using NELL
We describe an open information extraction system for biomedical text based on NELL (the Never-Ending Language Learner) (Carlson et al., 2010), a system designed for extraction from Web text. NELLExpand
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On the use of structural templates for high‐resolution docking
Reliable high‐resolution prediction of protein complex structures starting from the free monomers is a considerable challenge toward large‐scale mapping of the structural details of protein‐proteinExpand
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