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Lucas A. Salas
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2020 – today
- 2024
- [j6]Michael Y. Fatemi, Yunrui Lu, Alos Diallo
, Gokul Srinivasan, Zarif L. Azher, Brock C. Christensen, Lucas A. Salas
An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology. Briefings Bioinform. 25(6) (2024) - 2023
- [j5]Zarif L. Azher, Anish Suvarna, Ji-Qing Chen, Ze Zhang
Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication. BioData Min. 16(1) (2023) - 2022
- [j4]Shelby Bell-Glenn, Jeffrey A. Thompson
A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures. Frontiers Bioinform. 2 (2022) - [j3]Michael P. Mariani
MethylMasteR: A Comparison and Customization of Methylation-Based Copy Number Variation Calling Software in Cancers Harboring Large Scale Chromosomal Deletions. Frontiers Bioinform. 2 (2022) - [c3]Ramya Reddy, Ram Reddy, Cyril Sharma, Christopher R. Jackson, Scott Palisoul, Rachael Barney, Fred Kolling, Lucas A. Salas, Brock C. Christensen, Gabriel Brooks, Gregory Tsongalis, Louis J. Vaickus, Joshua J. Levy:
Graph Neural Networks Ameliorate Potential Impacts of Imprecise Large-Scale Autonomous Immunofluorescence Labeling of Immune Cells on Whole Slide Images. GeoMedIA 2022: 15-33 - [c2]Zarif L. Azher
Development of biologically interpretable multimodal deep learning model for cancer prognosis prediction. SAC 2022: 636-644 - 2020
- [j2]Joshua J. Levy
MethylNet: an automated and modular deep learning approach for DNA methylation analysis. BMC Bioinform. 21(1): 108 (2020) - [c1]Joshua J. Levy, Lucas A. Salas, Brock C. Christensen, Aravindhan Sriharan, Louis J. Vaickus:
PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation inDigital Pathology. PSB 2020: 403-414
2010 – 2019
- 2019
- [j1]Joshua J. Levy
PyMethylProcess - convenient high-throughput preprocessing workflow for DNA methylation data. Bioinform. 35(24): 5379-5381 (2019)
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