Keith Noto

According to our database1, Keith Noto authored at least 16 papers between 2004 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2022
Accurate genome-wide phasing from IBD data.
BMC Bioinform., 2022

2021
Ancestry inference using reference labeled clusters of haplotypes.
BMC Bioinform., 2021

2015
CSAX: Characterizing Systematic Anomalies in eXpression Data.
J. Comput. Biol., 2015

2014
Finding Novel Molecular Connections between Developmental Processes and Disease.
PLoS Comput. Biol., 2014

CSAX: Characterizing Systematic Anomalies in eXpression Data.
Proceedings of the Research in Computational Molecular Biology, 2014

2012
FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection.
Data Min. Knowl. Discov., 2012

2011
Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text.
BMC Bioinform., 2011

2010
Anomaly Detection Using an Ensemble of Feature Models.
Proceedings of the ICDM 2010, 2010

2009
The Transporter Classification Database: recent advances.
Nucleic Acids Res., 2009

2008
Learning Hidden Markov Models for Regression using Path Aggregation.
Proceedings of the UAI 2008, 2008

Learning classifiers from only positive and unlabeled data.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Learning to Find Relevant Biological Articles without Negative Training Examples.
Proceedings of the AI 2008: Advances in Artificial Intelligence, 2008

2007
Learning probabilistic models of <i>cis</i>-regulatory modules that represent logical and spatial aspects.
Bioinform., 2007

2006
A specialized learner for inferring structured cis-regulatory modules.
BMC Bioinform., 2006

2004
Learning Regulatory Network Models that Represent Regulator States and Roles.
Proceedings of the Regulatory Genomics, 2004


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