Author

L. A. Salas

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 3 Cancer Biology· 2

Signature Assays, Organisms & Methods

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Organism:human· 5 Research Focus:differential expression· 3 Assay:bulk RNA-seq· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:drug response / drug discovery· 2 Research Focus:gene regulatory network inference· 2

Frequent Co-Authors

J. Levy· 3 shared B. C. Christensen· 2 shared B. Christensen· 2 shared L. J. Vaickus· 2 shared A. A. Hippen· 1 shared A. Berchuck· 1 shared A. Campbell· 1 shared B. K. Dalley· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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3 shared papersPathology

J. Levy

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Molecular subtypes of high grade serous ovarian cancer across racial groups and gene expression platforms

N. R. Davidson, M. E. Barnard, A. A. Hippen, A. Campbell, C. Johnson, G. P. Way, B. K. Dalley, A. Berchuck, L. A. Salas, L. C. Peres, J. R. Marks, J. M. Schildkraut, C. S. Greene, J. A. Doherty

This study identifies molecular subtypes of high-grade serous ovarian cancer across racial groups and gene expression platforms, finding similar subtype-specific survival rates despite differences in subtype prevalence.

bioRxiv · Nov 1, 2023Cancer Biology

Normal gastric tissue Helicobacter pylori infection is associated with epigenetic age acceleration, increased mitotic tick rate, tissue cell composition, and Natural Killer cell methylation alterations

I. M. Vlasac, L. A. Salas, B. C. Christensen

The paper examines DNA methylation changes in normal gastric mucosa from H. pylori-infected individuals with and without gastric cancer, finding epigenetic age acceleration, increased mitotic activity, and immune cell composition differences.

bioRxiv · Jun 28, 2023 · PreprintCancer Biology

Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study

M. Fatemi, E. Feng, C. Sharma, Z. Azher, T. Goel, O. Ramwala, S. Palisoul, R. Barney, L. Perreard, F. Kolling, L. A. Salas, B. Christensen, G. Tsongalis, L. Vaickus, J. Levy

This study investigates using deep learning to predict spatial transcriptomics data from whole slide images to assess colorectal tumor metastasis, finding that convolutional networks outperform transformer and graph-based models.

bioRxiv · Nov 24, 2022 · PreprintPathology

Development of Biologically Interpretable Multimodal Deep Learning Model for Cancer Prognosis Prediction

Z. L. Azher, L. J. Vaickus, L. A. Salas, B. Christensen, J. Levy

This paper develops a multimodal deep learning model for cancer prognosis that integrates gene expression, DNA methylation, histopathological imaging, and clinical data, showing improved performance over unimodal approaches.

bioRxiv · Oct 30, 2021 · PreprintPathology

Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction using Spatially Localized Immuno-Oncology Markers

J. Levy, C. Bobak, M. Nasir-Moin, E. M. Veziroglu, S. M. Palisoul, R. E. Barney, L. A. Salas, B. C. Christensen, G. J. Tsongalis, L. J. Vaickus

This study uses mixed-effects machine learning to predict colon cancer metastasis by analyzing spatially localized immuno-oncology markers in tumor tissue.

bioRxiv · Aug 1, 2021Pathology