Fast Kernel Methods for SVM Sequence Classifiers. - Pavel P. Kuksa; Vladimir Pavlovic 001 (WABI, 2007)

On the Role of Local Matching for Efficient Semi-supervised Protein Sequence Classification. - Pavel P. Kuksa; Pai-Hsi Huang; Vladimir Pavlovic 001 (BIBM, 2008)

Fast protein homology and fold detection with sparse spatial sample kernels. - Pavel P. Kuksa; Pai-Hsi Huang; Vladimir Pavlovic 001 (ICPR, 2008)

Scalable Algorithms for String Kernels with Inexact Matching. - Pavel P. Kuksa; Pai-Hsi Huang; Vladimir Pavlovic 001 (NIPS, 2008)

Fast Motif Selection for Biological Sequences. - Pavel P. Kuksa; Vladimir Pavlovic 001 (BIBM, 2009)

Combining labeled and unlabeled data with word-class distribution learning. - Yanjun Qi; Ronan Collobert; Pavel P. Kuksa; Koray Kavukcuoglu; Jason Weston (CIKM, 2009)

Semi-Supervised Sequence Labeling with Self-Learned Features. - Yanjun Qi; Pavel P. Kuksa; Ronan Collobert; Kunihiko Sadamasa; Koray Kavukcuoglu; Jason Weston (ICDM, 2009)

Efficient use of unlabeled data for protein sequence classification: a comparative study. - Pavel P. Kuksa; Pai-Hsi Huang; Vladimir Pavlovic 001 (BMC Bioinform., 2009)

Efficient alignment-free DNA barcode analytics. - Pavel P. Kuksa; Vladimir Pavlovic 001 (BMC Bioinform., 2009)

Spatial Representation for Efficient Sequence Classification. - Pavel P. Kuksa; Vladimir Pavlovic 001 (ICPR, 2010)

Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction. - Pavel P. Kuksa; Yanjun Qi; Bing Bai; Ronan Collobert; Jason Weston; Vladimir Pavlovic 001; Xia Ning (ECML/PKDD (2), 2010)

Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning. - Pavel P. Kuksa; Yanjun Qi (SDM, 2010)

Efficient motif finding algorithms for large-alphabet inputs. - Pavel P. Kuksa; Vladimir Pavlovic 001 (BMC Bioinform., 2010)

Natural Language Processing (Almost) from Scratch. - Ronan Collobert; Jason Weston; Léon Bottou; Michael Karlen; Koray Kavukcuoglu; Pavel P. Kuksa (J. Mach. Learn. Res., 2011)

2D similarity kernels for biological sequence classification. - Pavel P. Kuksa (BIOKDD, 2012)

Efficient evaluation of large sequence kernels. - Pavel P. Kuksa; Vladimir Pavlovic 001 (KDD, 2012)

Generalized Similarity Kernels for Efficient Sequence Classification. - Pavel P. Kuksa; Imdadullah Khan; Vladimir Pavlovic 001 (SDM, 2012)

Biological Sequence Classification with Multivariate String Kernels. - Pavel P. Kuksa (IEEE ACM Trans. Comput. Biol. Bioinform., 2013)

Efficient multivariate sequence classification. - Pavel P. Kuksa (CoRR, 2014)

HIPPIE: a high-throughput identification pipeline for promoter interacting enhancer elements. - Yih-Chii Hwang; Chiao-Feng Lin; Otto Valladares; John Malamon; Pavel P. Kuksa; Qi Zheng; Brian D. Gregory; Li-San Wang (Bioinform., 2015)

High-order neural networks and kernel methods for peptide-MHC binding prediction. - Pavel P. Kuksa; Martin Renqiang Min; Rishabh Dugar; Mark Gerstein (Bioinform., 2015)

DASHR: database of small human noncoding RNAs. - Yuk Yee Leung; Pavel P. Kuksa; Alexandre Amlie-Wolf; Otto Valladares; Lyle H. Ungar; Sampath Kannan; Brian D. Gregory; Li-San Wang (Nucleic Acids Res., 2016)

SPAR: small RNA-seq portal for analysis of sequencing experiments. - Pavel P. Kuksa; Alexandre Amlie-Wolf; Zivadin Katanic; Otto Valladares; Li-San Wang; Yuk Yee Leung (Nucleic Acids Res., 2018)

DASHR 2.0: integrated database of human small non-coding RNA genes and mature products. - Pavel P. Kuksa; Alexandre Amlie-Wolf; Zivadin Katanic; Otto Valladares; Li-San Wang; Yuk Yee Leung (Bioinform., 2019)

SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants. - Pavel P. Kuksa; Chien-Yueh Lee; Alexandre Amlie-Wolf; Prabhakaran Gangadharan; Elizabeth E. Mlynarski; Yi-Fan Chou; Han-Jen Lin; Heather Issen; Emily Greenfest-Allen; Otto Valladares; Yuk Yee Leung; Li-San Wang (Bioinform., 2020)

hipFG: high-throughput harmonization and integration pipeline for functional genomics data. - Jeffrey Cifello; Pavel P. Kuksa; Naveensri Saravanan; Otto Valladares; Li-San Wang; Yuk Yee Leung (Bioinform., 2023)