51902-Johnson, Travis

Travis S. Johnson, PhD

Agnes Beaudry Investigator in Myeloma Research

Assistant Professor of Biostatistics & Health Data Science

Phone
(317) 278-5451
Address
HITS 3000
BSAT
IN
Indianapolis, IN
PubMed:
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CV:
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Key Publications

Liu, Y., Wang, T., Duggan, B., Huang, K., Zhang, J., Ye, X., Johnson, T.S. (2022). SPCS: A Spatial and Pattern Combined Smoothing Method for Spatial Transcriptomics Expression. Briefings in Bioinformatics.
Sharpnack, M. F.*, Johnson, T. S.*, Chalkley, R., Han, Z., Carbone, D., Huang, K., He, K. (2022). TSAFinder: Exhaustive Tumor Specific Antigen Detection with RNAseq. Bioinformatics.
Johnson, T. S., Christina, Y. Y., Huang, Z., Xu, S., Wang, T., Dong, C., ... & Zhang, Y. (2022). Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning framework for prioritizing cells in relation to disease. Genome Medicine,14(1), 1-23.
Huang, X., Huang, K., Johnson, T., Radovich, M., Zhang, J., Ma, J., & Wang, Y. (2021). ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways. NAR Genomics and Bioinformatics3(4), lqab097.
Xu, C., Sun, S., Johnson, T., Qi, R., Zhang, S., Zhang, J., & Yang, K. (2021). The glutathione peroxidase Gpx4 prevents lipid peroxidation and ferroptosis to sustain Treg cell activation and suppression of antitumor immunity. Cell Reports35(11), 109235.
Wang, T., Johnson, T. S., Shao, W., Lu, Z., Helm, B. R., Zhang, J., & Huang, K. (2019). BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes. Genome Biology20(1), 1-15.
Johnson, T.S., Wang, T., Huang, Z., Yu, C.Y., Wu, Y., Han, Y., Zhang, Y., Huang, K., Zhang, J. (2019). LAmbDA: Label Ambiguous Domain Adaptation Dataset Integration Reduces Batch Effects and Improves Subtype Detection. Bioinformatics, 35(22), 4696-4706.
Johnson, T.S.
, Li, S., Franz, E., Huang, Z., Li, S.D., Campbell, M.J., Huang, K., Zhang, Y. (2019). PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers. Gigascience, 8(5), giz046.

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