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» Probabilistic topic modeling for genomic data interpretation
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ISAMI
2010
14 years 7 months ago
Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
Sérgio A. D. Deusdado, Paulo Carvalho
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
15 years 9 months ago
Multiscale topic tomography
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...
ISMB
2000
14 years 10 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
TREC
2007
14 years 10 months ago
Language Models for Genomics Information Retrieval: UIUC at TREC 2007 Genomics Track
The University of Illinois at Urbana-Champaign (UIUC) participated in TREC 2007 Genomics Track. Our general goal of participation is to apply language modelbased approaches to the...
Yue Lu, Jing Jiang, Xu Ling, Xin He, ChengXiang Zh...
SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
15 years 6 months ago
Topic Evolution in a Stream of Documents.
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Alexander Hinneburg, Andrè Gohr, Myra Spili...