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Derek Reiman
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2020 – today
- 2024
- [c7]Leah L. Weber
, Derek Reiman
TRIBAL: Tree Inference of B Cell Clonal Lineages. RECOMB 2024: 364-367 - 2021
- [j4]Derek Reiman
MiMeNet: Exploring microbiome-metabolome relationships using neural networks. PLoS Comput. Biol. 17(5) (2021) - [j3]Derek Reiman
Pseudocell Tracer - A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination. PLoS Comput. Biol. 17(5) (2021) - [c6]Tina Khajeh, Derek Reiman
Integrating microbiome and metabolome data for host disease prediction via deep neural networks. BHI 2021: 1-4 - [p1]Derek Reiman
Predicting Host Phenotype Based on Gut Microbiome Using a Convolutional Neural Network Approach. Artificial Neural Networks, 3rd Edition 2021: 249-266 - [i1]Derek Reiman
Meta-Signer: Metagenomic Signature Identifier based onrank aggregation of features. F1000Research 10: 194 (2021) - 2020
- [j2]Derek Reiman
PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolutional Neural Networks to Predict Host Phenotype From Metagenomic Data. IEEE J. Biomed. Health Informatics 24(10): 2993-3001 (2020) - [c5]Derek Reiman, Yang Dai:
Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets. DeLTA 2020: 103-110
2010 – 2019
- 2019
- [j1]Ahmed A. Metwally
Utilizing longitudinal microbiome taxonomic profiles to predict food allergy via Long Short-Term Memory networks. PLoS Comput. Biol. 15(2) (2019) - [c4]Derek Reiman
Using Autoencoders for Predicting Latent Microbiome Community Shifts Responding to Dietary Changes. BIBM 2019: 1884-1891 - [c3]Jingting Xu, Derek Reiman
Using Convolutional Neural Network to Study the Regulatory Relationship Between DNA Methylation and Gene Expression. BIBM 2019: 2399-2404 - [c2]Derek Reiman, Lingdao Sha, Irvin Ho, Timothy Tan, Denise Lau, Aly A. Khan:
Integrating RNA expression and visual features for immune infiltrate prediction. PSB 2019: 284-295 - 2017
- [c1]Derek Reiman
Using convolutional neural networks to explore the microbiome. EMBC 2017: 4269-4272
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