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2020 – today
- 2022
[j10]Keith Noto, Luong Ruiz:
Accurate genome-wide phasing from IBD data. BMC Bioinform. 23(1): 502 (2022)- 2021
- [j9]Yong Wang
, Shiya Song, Joshua G. Schraiber, Alisa Sedghifar, Jake K. Byrnes, David A. Turissini, Eurie L. Hong, Catherine A. Ball, Keith Noto:
Ancestry inference using reference labeled clusters of haplotypes. BMC Bioinform. 22(1): 459 (2021)
2010 – 2019
- 2015
- [j8]Keith Noto, Saeed Majidi, Andrea G. Edlow, Heather C. Wick, Diana W. Bianchi, Donna K. Slonim:
CSAX: Characterizing Systematic Anomalies in eXpression Data. J. Comput. Biol. 22(5): 402-413 (2015) - 2014
- [j7]Jisoo Park, Heather C. Wick, Daniel E. Kee, Keith Noto, Jill L. Maron, Donna K. Slonim:
Finding Novel Molecular Connections between Developmental Processes and Disease. PLoS Comput. Biol. 10(5) (2014) - [c6]Keith Noto, Carla E. Brodley, Saeed Majidi, Diana W. Bianchi, Donna K. Slonim:
CSAX: Characterizing Systematic Anomalies in eXpression Data. RECOMB 2014: 222-236 - 2012
- [j6]Keith Noto, Carla E. Brodley, Donna K. Slonim:
FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection. Data Min. Knowl. Discov. 25(1): 109-133 (2012) - [i1]Keith Noto, Mark Craven:
Learning Hidden Markov Models for Regression using Path Aggregation. CoRR abs/1206.3275 (2012) - 2011
- [j5]Martin Krallinger, Miguel Vazquez, Florian Leitner, David Salgado, Andrew Chatr-aryamontri, Andrew G. Winter, Livia Perfetto, Leonardo Briganti, Luana Licata, Marta Iannuccelli, Luisa Castagnoli, Gianni Cesareni, Mike Tyers, Gerold Schneider, Fabio Rinaldi, Robert Leaman, Graciela Gonzalez, Sérgio Matos, Sun Kim, W. John Wilbur, Luis M. Rocha, Hagit Shatkay, Ashish V. Tendulkar, Shashank Agarwal, Feifan Liu, Xinglong Wang, Rafal Rak, Keith Noto, Charles Elkan, Zhiyong Lu:
The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text. BMC Bioinform. 12(S-8): S3 (2011) - [j4]Aditya Kumar Sehgal, Sanmay Das, Keith Noto, Milton H. Saier Jr., Charles Elkan:
Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 8(3): 851-857 (2011) - 2010
- [c5]Keith Noto, Carla E. Brodley, Donna K. Slonim:
Anomaly Detection Using an Ensemble of Feature Models. ICDM 2010: 953-958
2000 – 2009
- 2009
- [j3]Milton H. Saier Jr., Ming Ren Yen, Keith Noto, Dorjee G. Tamang, Charles Elkan:
The Transporter Classification Database: recent advances. Nucleic Acids Res. 37(Database-Issue): 274-278 (2009) - 2008
- [c4]Keith Noto, Milton H. Saier Jr., Charles Elkan:
Learning to Find Relevant Biological Articles without Negative Training Examples. Australasian Conference on Artificial Intelligence 2008: 202-213 - [c3]Charles Elkan, Keith Noto:
Learning classifiers from only positive and unlabeled data. KDD 2008: 213-220 - [c2]Keith Noto, Mark Craven:
Learning Hidden Markov Models for Regression using Path Aggregation. UAI 2008: 444-451 - 2007
- [j2]Keith Noto, Mark Craven:
Learning probabilistic models of cis-regulatory modules that represent logical and spatial aspects. Bioinform. 23(2): 156-162 (2007) - 2006
- [j1]Keith Noto, Mark Craven:
A specialized learner for inferring structured cis-regulatory modules. BMC Bioinform. 7: 528 (2006) - 2004
- [c1]Keith Noto, Mark Craven:
Learning Regulatory Network Models that Represent Regulator States and Roles. Regulatory Genomics 2004: 52-64
Coauthor Index
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