Author

Brent Cochran

Tufts UniversityORCID 0000-0002-7598-5604Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Approach:deep learning· 1 Assay:DNA methylation· 1 Assay:protein sequence· 1

Frequent Co-Authors

Nataša Miškov-ŽivanoviD· 3 shared Niloofar Arazkhani· 2 shared Difei TangiD· 1 shared Emilee HoltzappleiD· 1 shared Haomiao Luo· 1 shared Wangxin XiaoiD· 1 shared Weijia XiaoiD· 1 shared Xue ZhangiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 10 mutual co-author links

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3 shared papersSystems Biology

Nataša Miškov-ŽivanovORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

BELL: Biomodel Evidence and LLM-based Logic

Niloofar Arazkhani, Brent Cochran, Nataša Miškov-Živanov

BELL automates evidence retrieval and scoring for biological interactions, achieving high confidence in 49.5% of tested interactions and guiding curators effectively.

bioRxiv · Sep 20, 2026 · PreprintBioinformatics

GBM model refinement with literature curation, rule-based NLP, and LLMs

Niloofar Arazkhani, Haomiao Luo, Difei Tang, Brent Cochran, Nataša Miškov-Živanov

This work improves a GBM mechanistic model and evaluates NLP and LLM approaches for model refinement using graph metrics and literature curation.

bioRxiv · Mar 27, 2025 · PreprintSystems Biology

DeEPsnap: human essential gene prediction by integrating multi-omics data

Xue Zhang, Weijia Xiao, Brent Cochran, Wangxin Xiao

DeEPsnap predicts human essential genes by integrating multi-omics data using a snapshot ensemble deep neural network, achieving high accuracy in cross-validation.

bioRxiv · Jun 20, 2024 · PreprintBioinformatics

Automated verification, assembly, and extension of GBM stem cell network model with knowledge from literature and data

Emilee Holtzapple, Brent Cochran, Nataša Miškov-Živanov

This paper develops automated methods to verify and assemble a GBM stem cell signaling network, showing that automated approaches lack precision and realistic topology compared to hybrid methods.

bioRxiv · Jul 4, 2021 · PreprintSystems Biology