Travis S. Johnson

发表

BERMUDA: A novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes

Kun Huang, Jie Zhang, Wei Shao, 2019 .

A protocol to evaluate RNA sequencing normalization methods

Philip R. O. Payne, Kun Huang, Travis S. Johnson, 2019, BMC Bioinformatics.

SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer

Maher Rizkalla, Jie Zhang, Zhi Huang, 2019, Front. Genet..

Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning framework for prioritizing cells in relation to disease

Zhi Huang, Kun Huang, Yijie Wang, 2020, bioRxiv.

Estimation of Neural Cell types in the Allen Human Brain Atlas using Murine-derived Expression Profiles

Travis S. Johnson, 2016 .

Functional Virtual Flow Cytometry: A Visual Analytic Approach for Characterizing Single-Cell Gene Expression Patterns

Travis S. Johnson, Zhi Han, Jie Zhang, 2017, BioMed research international.

BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes

Travis S. Johnson, Jie Zhang, Kun Huang, 2019, Genome Biology.

Pseudogene-gene functional networks are prognostic of patient survival in breast cancer

Travis S. Johnson, Kun Huang, Sasha Smerekanych, 2020, BMC Medical Genomics.

PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers

Zhi Huang, Kun Huang, Yan Zhang, 2019, GigaScience.

Gene Co-expression Network and Copy Number Variation Analyses Identify Transcription Factors Associated With Multiple Myeloma Progression

Kun Huang, Travis S. Johnson, Zhi Han, 2019, Front. Genet..

Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease

Travis S. Johnson, Christina Y. Yu, Jie Zhang, 2020, Genome Medicine.

Spatial cell type composition in normal and Alzheimers human brains is revealed using integrated mouse and human single cell RNA sequencing

Travis S. Johnson, Zachary B. Abrams, R. Machiraju, 2020, Scientific Reports.

Lack of human cytomegalovirus expression in single cells from glioblastoma tumors and cell lines

Travis S. Johnson, Zachary B. Abrams, Kun Huang, 2017, Journal of NeuroVirology.

Combinatorial analyses reveal that cellular composition changes have different impact on transcriptomic changes of cell type specific genes in Alzheimer’s Disease brains

Travis S. Johnson, Jie Zhang, Kun Huang, 2020 .

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations

Maher Rizkalla, Zhi Huang, Kun Huang, 2020, BMC Medical Genomics.

LAmbDA: Label Ambiguous Domain Adaption Dataset Integration Reduces Batch Effects and Improves Subtype Detection

Zhi Huang, Jie Zhang, Yi Wu, 2019, bioRxiv.

AIscEA: Unsupervised Integration of Single-cell Gene Expression and Chromatin Accessibility via Their Biological Consistency

Travis S. Johnson, Yue Wang, Kun Huang, 2022, bioRxiv.

BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes

Travis S. Johnson, Kun Huang, J. Zhang, 2019, Genome Biology.

Clinical and Molecular Correlates of Tumor Mutation Burden in Non-Small Cell Lung Cancer.

Travis S. Johnson, Michael F. Sharpnack, D. Carbone, 2020, Lung cancer.

Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease

Travis S. Johnson, Jie Zhang, Kun Huang, 2020, Scientific Reports.

Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease

Travis S. Johnson, Christina Y. Yu, Jie Zhang, 2022, Genome Medicine.

Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers

Travis S. Johnson, Jie Zhang, Kun Huang, 2022, Cancers.

ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways

Travis S. Johnson, Jianzhu Ma, Jie Zhang, 2021, NAR genomics and bioinformatics.

Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials

Kun Huang, Travis S. Johnson, Sihong Li, 2018, PSB.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

Travis S. Johnson, Michael F. Sharpnack, Jie Zhang, 2021, bioRxiv.

Optimal Transport-Based Early Detection of Mild Cognitive Impairment Patients Based on Magnetic Resonance Images

Travis S. Johnson, Jie Zhang, Kun Huang, 2021 .

Diagnostic Evidence Gauge of Spatial Transcriptomics (DEGAS): Using transfer learning to map clinical data to spatial transcriptomics in prostate cancer

Travis S. Johnson, J Zhang, Kun Huang, 2023, bioRxiv.

Optimal transport- and kernel-based early detection of mild cognitive impairment patients based on magnetic resonance and positron emission tomography images

Travis S. Johnson, Jie Zhang, Kun Huang, 2022, Alzheimer's research & therapy.

Enhanced microglial dynamics and paucity of tau seeding in the amyloid plaque microenvironment contributes to cognitive resilience in Alzheimer’s disease

Travis S. Johnson, J Zhang, J. Troncoso, 2023, bioRxiv.

Integration of Mouse and Human Single-cell RNA Sequencing Infers Spatial Cell-type Composition in Human Brains

Raghu Machiraju, Kun Huang, Travis S. Johnson, 2019, bioRxiv.

Topological Methods for Visualization and Analysis of High Dimensional Single-Cell RNA Sequencing Data

Travis S. Johnson, Jie Zhang, Kun Huang, 2018, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

Topological Methods for Visualization and Analysis of High Dimensional Single-Cell RNA Sequencing Data

Tongxin Wang, Jie Zhang, Kun Huang, 2018, PSB.

Identifying 1q amplification and PHF19 expressing high-risk cells associated with relapsed/refractory multiple myeloma

Travis S. Johnson, V. Chopra, R. Abonour, 2023, Research square.

PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers

Travis S. Johnson, Kun Huang, M. Campbell, 2019, GigaScience.

Abstract 238: Exhaustive tumor specific antigen detection with RNAseq

Travis S. Johnson, Michael F. Sharpnack, Zhi Han, 2021, Bioinformatics and Systems Biology.

LAmbDA: label ambiguous domain adaptation dataset integration reduces batch effects and improves subtype detection

Zhi Huang, Kun Huang, Tongxin Wang, 2019, Bioinform..

Diagnostic Evidence Gauge of Spatial Transcriptomics (DEGAS): Using transfer learning to map clinical data

Travis S. Johnson, J Zhang, A. Alomari, 2023 .