RegulomeAtlas: Interactive Molecular Mechanism Database with Guided Case Studies
A curated, interactive HTML/JavaScript template library that researchers and educators can deploy on their own institutional servers or websites. Each template covers a specific regulatory mechanism (e.g., 'miRNA binding in 3' UTR → mRNA stability loss → reduced protein output') with embedded molecular diagrams, real experimental data visualizations, interactive sliders showing how sequence changes affect binding affinity, and 3–5 worked case studies from published papers with annotations explaining the mechanistic chain from DNA → UTR → protein fold outcome.
28 weeks • 70% confidence
Value Proposition
Eliminates fragmentation by bundling mechanism + data + annotation in one deployable, customizable artifact. Researchers get a single, coherent mental model instead of hunting across 12 papers. Templates are self-hosted so institutions keep data private and avoid SaaS lock-in. Faster experimental design because scientists reference the mechanism guide before running qPCR or ribosome profiling experiments.
Target Audience
PhD students, postdocs, and junior faculty in molecular biology labs; biology department instructors designing curricula; biotech company research teams onboarding new scientists.
Key Features
- Pre-built interactive diagrams for 15 core mechanisms (Kozak sequence, IRES, intron-mediated enhancement, nonsense-mediated decay, polyA tail effects, secondary structure effects on translation)
- Embedded real experimental datasets (RNA-seq, ribosome profiling, proteomics) with annotations explaining each result in mechanistic terms
- Customizable case-study templates researchers can populate with their own data
- And more, with full implementation detail...
Tech Stack
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Sign up freeOriginal Problem
Molecular biologists struggle to understand and predict how genetic regulatory elements affect protein expression and foldingResearchers and students in molecular biology lack clear, accessible explanations of how UTRs (untranslated regions) and introns mechanistically regulate gene expression and influence downstream protein folding outcomes. Current educational resources and documentation are fragmented across textbooks, papers, and forums, forcing researchers to piece together understanding from multiple sources, leading to knowledge gaps that impact experimental design and interpretation.
Score: 17.5%