A computational approach toward label-free protein quantification using predicted peptide detectability. - Haixu Tang; Randy J. Arnold; Pedro Alves; Zhiyin Xun; David E. Clemmer; Milos V. Novotny; James P. Reilly; Predrag Radivojac (ISMB (Supplement of Bioinformatics), 2006)

A Machine Learning Approach to Predicting Peptide Fragmentation Spectra. - Randy J. Arnold; Narmada Jayasankar; Divya Aggarwal; Haixu Tang; Predrag Radivojac (Pacific Symposium on Biocomputing, 2006)

Advancement in Protein Inference from Shotgun Proteomics Using Peptide Detectability. - Pedro Alves; Randy J. Arnold; Milos V. Novotny; Predrag Radivojac; James P. Reilly; Haixu Tang (Pacific Symposium on Biocomputing, 2007)

Fast and accurate identification of semi-tryptic peptides in shotgun proteomics. - Pedro Alves; Randy J. Arnold; David E. Clemmer; Yixue Li; James P. Reilly; Quanhu Sheng; Haixu Tang; Zhiyin Xun; Rong Zeng; Predrag Radivojac (Bioinform., 2008)

A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics. - Yong Fuga Li; Randy J. Arnold; Yixue Li; Predrag Radivojac; Quanhu Sheng; Haixu Tang (J. Comput. Biol., 2009)

Improving phosphopeptide identification in shotgun proteomics by supervised filtering of peptide-spectrum matches. - Sujun Li; Randy J. Arnold; Haixu Tang; Predrag Radivojac (BCB, 2013)

A maximum-likelihood approach to absolute protein quantification in mass spectrometry. - Chao Ji; Yong Fuga Li; Earl P. Bellinger; Sujun Li; Randy J. Arnold; Predrag Radivojac; Haixu Tang (BCB, 2015)