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High-throughput Unmasking of Biological Interactomes with Binding Landscape Emulators (HUBBLE)

Solicitation ID: DARPA-PA-27-01

Agency: DARPA

Type: Solicitation
Deadline: 2026-11-05T15:00:00 ET
Eligibility: Maybe (OTA/Consortium)
Funding: N/A
Doc Type: Other
Clearance: CUI
Program Manager: N/A
Last Updated: 2026-10-09 16:04
Analyzed File: Attachment_B_DARPA-PA-26-10__Model_OT_for_Research_HUBBLE_20261008.docx

Eligibility Reasoning

This Agreement is an “other transaction” pursuant to 10 U.S.C. § 4021... Performer (Prime Contractor) represents that it is eligible for the award of this Agreement under 10 U.S.C. § 4022(d)(1)(A) because at least one nontraditional defense contractor or nonprofit research institution is participating to a significant extent in this Agreement (Partner):

Note: This is an AI-generated summary...

Summary

This document is a model Other Transaction (OT) agreement for the Defense Advanced Research Projects Agency (DARPA) HUBBLE (High-throughput Unmasking of Biological Interactomes with Binding Landscape Emulators) program. The program's objective is to develop an in-silico capability for the high-throughput mapping of all protein-protein interactions. This capability is intended to be used to identify novel diagnostic and therapeutic targets, with a specific demonstration focused on the interaction space underlying traumatic brain injury (TBI). The provided document serves as a template for the research agreement, detailing the legal and administrative terms and conditions, including project scope, management, payment schedules, intellectual property rights, data rights, and cybersecurity requirements for performers.

Overall Technical Areas

Computational BiologyIn-Silico ModelingProtein-Protein Interaction MappingHigh-Throughput Data AnalysisBiological Interactome AnalysisMolecular Binding EmulationTherapeutic Target IdentificationDiagnostic Target DiscoveryTraumatic Brain Injury ModelingMachine Learning for BiologyBioinformatics Algorithm DevelopmentSystems BiologyProteomics

Probable LBNL Areas

N/A

Focus Areas

nan

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

NameScoreOrganization
Maciej Haranczyk0.77CSA | AMCR | Computer Science · In-Silico Modeling
Zhong Wang0.76BSA | DOE Joint Genome Institute | Data Science & Informatics · Bioinformatics Algorithm Development
Sharon Greenblum0.76BSA | DOE Joint Genome Institute | JGI Technology Dept · Systems Biology
Morgan Price0.76BSA | Env. Genomics & Sys. Biology | Comparative and Funct Genomics · Computational Biology
Georgios Pavlopoulos0.76BSA | DOE Joint Genome Institute | JGI Science Dept · Machine Learning for Biology
Christopher Petzold0.75BSA | Biological Systems & Engineering | Biodesign Dept · Proteomics
Piotr Zarzycki0.74EESA | EG | Geochemistry Dept · Molecular Binding Emulation
Banumathi Sankaran0.73BSA | Molecular Biophysics & Integrated Bioimaging | Structural Biology Dept · Protein-Protein Interaction Mapping
Zhi Jackie Yao0.72CSA | AMCR | Applied Mathematics · Traumatic Brain Injury Modeling
Momoe Kato0.72BSA | Env. Genomics & Sys. Biology | Comparative and Funct Genomics · Therapeutic Target Identification

Fundamental Research Exemption (FRE)

At this time, DARPA expects the work performed under this Agreement to be fundamental research, and it is, therefore, not subject to publication restrictions. Papers resulting from unclassified contracted fundamental research are exempt from prepublication controls and requirements, pursuant to DoD Instruction 5230.27 dated November 18, 2016.