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Christina S. Leslie
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2020 – today
- 2023
- [c15]Dig Vijay Kumar Yarlagadda
, Joan Massagué, Christina S. Leslie:
Discrete Representation Learning for Modeling Imaging-based Spatial Transcriptomics Data. ICCV (Workshops) 2023: 3848-3857
2010 – 2019
- 2019
- [c14]Christina S. Leslie:
Decoding Epigenomic Programs in Immunity and Cancer. BCB 2019: 2-3 - 2018
- [j21]Shih-Han Lee, Irtisha Singh
Widespread intronic polyadenylation inactivates tumour suppressor genes in leukaemia. Nat. 561(7721): 127-131 (2018) - 2017
- [r2]William Stafford Noble, Christina S. Leslie:
Learning Models of Biological Sequences. Encyclopedia of Machine Learning and Data Mining 2017: 723-729 - 2016
- [j20]Yuheng Lu, Christina S. Leslie:
Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data. PLoS Comput. Biol. 12(7) (2016) - 2015
- [j19]Manu Setty, Christina S. Leslie:
SeqGL Identifies Context-Dependent Binding Signals in Genome-Wide Regulatory Element Maps. PLoS Comput. Biol. 11(5) (2015) - 2011
- [j18]Iain Melvin, Jason Weston, William Stafford Noble, Christina S. Leslie:
Detecting Remote Evolutionary Relationships among Proteins by Large-Scale Semantic Embedding. PLoS Comput. Biol. 7(1) (2011) - [c13]Christina S. Leslie:
Keynote: High-resolution sequence and chromatin signatures predict transcription factor binding in the human genome. ICCABS 2011: 2 - 2010
- [j17]Guy Nimrod, Maya Schushan, András Szilágyi
iDBPs: a web server for the identification of DNA binding proteins. Bioinform. 26(5): 692-693 (2010) - [j16]Xuejing Li, Casandra Panea, Chris H. Wiggins, Valerie Reinke, Christina S. Leslie:
Learning "graph-mer" Motifs that Predict Gene Expression Trajectories in Development. PLoS Comput. Biol. 6(4) (2010) - [j15]Phaedra Agius, Aaron Arvey
High Resolution Models of Transcription Factor-DNA Affinities Improve In Vitro and In Vivo Binding Predictions. PLoS Comput. Biol. 6(9) (2010) - [r1]William Stafford Noble, Christina S. Leslie:
Learning Models of Biological Sequences. Encyclopedia of Machine Learning 2010: 590-594
2000 – 2009
- 2009
- [j14]Iain Melvin, Jason Weston, Christina S. Leslie, William Stafford Noble:
RANKPROP: a web server for protein remote homology detection. Bioinform. 25(1): 121-122 (2009) - 2008
- [j13]Iain Melvin, Jason Weston, Christina S. Leslie, William Stafford Noble:
Combining classifiers for improved classification of proteins from sequence or structure. BMC Bioinform. 9 (2008) - [j12]Anshul Kundaje
A Predictive Model of the Oxygen and Heme Regulatory Network in Yeast. PLoS Comput. Biol. 4(11) (2008) - [c12]Doron Betel, Christina S. Leslie, Nikolaus Rajewsky:
Session Introduction. Pacific Symposium on Biocomputing 2008: 49-51 - 2007
- [j11]Gal Chechik, Christina S. Leslie, William Stafford Noble, Gunnar Rätsch
NIPS workshop on New Problems and Methods in Computational Biology. BMC Bioinform. 8(S-10) (2007) - [j10]Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie:
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition. BMC Bioinform. 8(S-4) (2007) - [j9]Iain Melvin, Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie:
Multi-class Protein Classification Using Adaptive Codes. J. Mach. Learn. Res. 8: 1557-1581 (2007) - 2006
- [j8]Anshul Kundaje
A classification-based framework for predicting and analyzing gene regulatory response. BMC Bioinform. 7(S-1) (2006) - [j7]Jason Weston, Rui Kuang, Christina S. Leslie, William Stafford Noble:
Protein Ranking by Semi-Supervised Network Propagation. BMC Bioinform. 7(S-1) (2006) - [p1]Jason Weston, Christina S. Leslie, Eugene Ie, William Stafford Noble:
Semi-Supervised Protein Classification Using Cluster Kernels. Semi-Supervised Learning 2006: 342-360 - 2005
- [j6]Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble:
Semi-supervised protein classification using cluster kernels. Bioinform. 21(15): 3241-3247 (2005) - [j5]Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie:
Motif-based protein ranking by network propagation. Bioinform. 21(19): 3711-3718 (2005) - [j4]Anshul Kundaje
Combining Sequence and Time Series Expression Data to Learn Transcriptional Modules. IEEE ACM Trans. Comput. Biol. Bioinform. 2(3): 194-202 (2005) - [c11]Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie:
Multi-class protein fold recognition using adaptive codes. ICML 2005: 329-336 - [c10]Manuel Middendorf, Anshul Kundaje
Motif Discovery Through Predictive Modeling of Gene Regulation. RECOMB 2005: 538-552 - 2004
- [j3]Christina S. Leslie, Eleazar Eskin, Adiel Cohen, Jason Weston, William Stafford Noble:
Mismatch string kernels for discriminative protein classification. Bioinform. 20(4): 467-476 (2004) - [j2]Rui Kuang, Christina S. Leslie, An-Suei Yang
Protein backbone angle prediction with machine learning approaches. Bioinform. 20(10): 1612-1621 (2004) - [j1]Christina S. Leslie, Rui Kuang:
Fast String Kernels using Inexact Matching for Protein Sequences. J. Mach. Learn. Res. 5: 1435-1455 (2004) - [c9]Rui Kuang, Eugene Ie, Ke Wang, Kai Wang, Mahira Siddiqi, Yoav Freund, Christina S. Leslie:
Profile-Based String Kernels for Remote Homology Detection and Motif Extraction. CSB 2004: 152-160 - [c8]Manuel Middendorf, Anshul Kundaje
Predicting genetic regulatory response using classification. ISMB/ECCB (Supplement of Bioinformatics) 2004: 232-240 - [c7]Manuel Middendorf, Anshul Kundaje
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response. Regulatory Genomics 2004: 1-13 - 2003
- [c6]Christina S. Leslie, Rui Kuang:
Fast Kernels for Inexact String Matching. COLT 2003: 114-128 - [c5]Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble:
Semi-supervised Protein Classification Using Cluster Kernels. NIPS 2003: 595-602 - 2002
- [c4]Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble:
A Kernel Approach for Learning from almost Orthogonal Patterns. ECML 2002: 511-528 - [c3]Christina S. Leslie, Eleazar Eskin, Jason Weston, William Stafford Noble:
Mismatch String Kernels for SVM Protein Classification. NIPS 2002: 1417-1424 - [c2]Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble:
A Kernel Approach for Learning from Almost Orthogonal Patterns. PKDD 2002: 494-511 - [c1]Christina S. Leslie, Eleazar Eskin, William Stafford Noble:
The Spectrum Kernel: A String Kernel for SVM Protein Classification. Pacific Symposium on Biocomputing 2002: 566-575
Coauthor Index
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