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Biosensors|March 29, 2023
Nucleic Acid Quantification by Multi-Frequency Impedance Cytometry and Machine LearningMahtab Kokabi, Jianye Sui, Neeru Gandotra, et al.BMC Medical Genomics|November 19, 2025
Improving newborn screening accuracy through genome sequencing, targeted metabolomics, and machine learningYuhan Xie, Gang Peng, Irina Tikhonova, et al.Genome Medicine|May 31, 2013
Multiplex target capture with double-stranded DNA probesPeidong Shen, Wenyi Wang, Aung-Kyaw Chi, et al.Science (New York, N.Y.)|April 27, 2002
Evolutionary rate in the protein interaction networkHunter B Fraser, Aaron E Hirsh, Lars M Steinmetz, et al.International Journal of Neonatal Screening|March 20, 2020
Reducing False-Positive Results in Newborn Screening Using Machine LearningGang Peng, Yishuo Tang, Tina M Cowan, et al.Nature|January 4, 2003
Role of duplicate genes in genetic robustness against null mutationsZhenglong Gu, Lars M Steinmetz, Xun Gu, et al.Human Genetics|October 13, 2021
The population genetics characteristics of a 90 locus panel of microhaplotypesAndrew J Pakstis, Neeru Gandotra, William C Speed, et al.Molecular Genetics and Metabolism|November 19, 2018
Elevated methylmalonic acidemia (MMA) screening markers in Hispanic and preterm newbornsGang Peng, Christina A de Fontnouvelle, Gregory M Enns, et al.Journal of Inherited Metabolic Disease|March 28, 2020
Ethnic variability in newborn metabolic screening markers associated with false-positive outcomesGang Peng, Yishuo Tang, Neeru Gandotra, et al.Journal of Inherited Metabolic Disease|January 21, 2023
Validation of a targeted metabolomics panel for improved second-tier newborn screeningJustin Mak, Gang Peng, Anthony Le, et al.Pageof 5