Author

Miles D Woodcock-Girard

University of Illinois at Chicago;ORCID 0009-0004-4548-8078Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Systems Biology· 2

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Assay:proteomics· 2 Research Focus:cell type annotation· 1 Organism:human· 1 Organism:mouse· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Kevin DrewiD· 2 shared Samantha N FischeriD· 2 shared Akshaya RajaramaniD· 1 shared Erin R. ClausseniD· 1 shared Riddhiman K GargeiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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2 shared papersSystems Biology

Kevin DrewORCID

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2 papers

Recent·Most cited

stem.MAP: Identification of cell-type-specific protein complexes in mammalian embryonic stem cells.

Akshaya Rajaraman, Samantha N Fischer, Miles D Woodcock-Girard, Riddhiman K Garge, Kevin Drew

The paper develops a proteomics-based machine learning workflow to identify cell-type-specific protein complexes in mouse embryonic stem cells, revealing 3,986 complexes and 1,388 unique interactions specific to mESC.

bioRxiv · Nov 6, 2026 · PreprintSystems Biology

DirectContacts2: A network of direct physical protein interactions derived from high-throughput mass spectrometry experiments

Erin R. Claussen, Miles D Woodcock-Girard, Susan M. Fischer, Kevin Drew

DirectContacts2 identifies direct protein interactions using mass spectrometry data and machine learning, improving accuracy over existing resources and providing structural models for disease-related complexes.

bioRxiv · Jul 17, 2025 · PreprintSystems Biology