Dana Movshovitz-Attias

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Marti A. Hearst15
Oren Etzioni11
Stephen Soderland11
Anthony Fader11
Fernando Pereira11
8William W. Cohen
7Ora Schueler-Furman
6Sergio Orduz
6Jaime Parra-Suescún
6Nikolay V Dokholyan

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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 an unstructured, flexible peptide to a rigid, well-defined bound structure? A structure-based analysis of peptide-protein interactions unravels that most peptides… (More)
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 a significant portion of the helpful answers, and so identifying users that have the potential of becoming strong contributers is an important task for owners… (More)
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 an excellent starting point for the characterization of the binding specificity of a given peptide-binding domain. A number of different protocols have recently been… (More)
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 the highly frequent appearances of certain patterns in a project to infer rules. It is known that if a pattern does not appear frequently enough, rules are not… (More)
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 of their origin domain by mimicking its mode of binding to cognate partners, and could serve as promising leads for rational design of inhibitory drugs. For our… (More)
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 of predicting code, while mainly ignoring the prediction of programmer comments. In this work, we predict comments from JAVA source files of open source projects,… (More)
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) (Carl-son et al., 2010), a system designed for extraction from Web text. NELL uses a coupled semi-supervised bootstrapping approach to learn new facts from text, given an initial ontology and a small number of " seeds " for each ontology… (More)
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-protein interactions. The current major bottleneck is to model the conformational changes of the monomer backbone upon binding. We evaluate the use of homolog structures… (More)
Alignment-HMM-based Extraction of Abbreviations from Biomedical Text
We present an algorithm for extracting abbreviation definitions from biomedical text. Our approach is based on an alignment HMM, matching abbreviations and their definitions. We report 98% precision and 93% recall on a standard data set, and 95% precision and 91% recall on an additional test set. Our results show an improvement over previously reported… (More)
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 hierarchy of categories and relations between them. The system then extracts facts that match the predefined ontology. We propose an unsupervised model that jointly… (More)