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GP-BT-1BQK7YKBiotechnologyOpen for request

Climate-resilient crop gene evidence explorer

An evidence explorer linking crop genes and genomic regions to drought, salinity, heat, flooding, and related resilience traits using curated public studies and databases.

  • Nuxt
  • Vue
  • FastAPI
  • PostgreSQL
  • Python
  • Biopython
  • Elasticsearch
  • Docker

Project definition

Problem statement

Crop-resilience evidence is spread across species, assemblies, gene identifiers, stress definitions, tissues, growth stages, experiments, and publication types. Similar gene names do not guarantee equivalent biological function.

The engineering problem is to normalise these records, grade the strength of each gene-trait claim, preserve study context, and distinguish direct experimental evidence from computational or cross-species inference.

Project objectives

  • Define controlled crop, gene, genomic-region, stress, trait, tissue, stage, treatment, and evidence vocabularies.
  • Curate permitted public studies and database records with complete citation and identifier provenance.
  • Map gene identifiers across supported genome versions and link orthologues under documented methods.
  • Grade evidence by study design, replication, phenotype, molecular support, and directness.
  • Search and compare candidate genes without presenting the result as a breeding or editing recommendation.

System design

System modules

01

Evidence curator

Captures study, crop, genotype, gene, stress, treatment, phenotype, method, result, and curator decision.

02

Identifier normaliser

Maps gene symbols, accessions, assembly versions, chromosome locations, and aliases.

03

Orthology module

Links selected cross-species homologues and records algorithm, confidence, and source.

04

Evidence scorer

Applies a transparent rubric to direct experiments, association studies, expression, and computational inference.

05

Evidence explorer

Provides gene and trait search, filters, networks, chromosome locations, study comparison, and citation traceability.

Methodology

System workflow

  1. 01
    Register sources

    The student selects public studies and database records under a fixed crop and stress scope.

  2. 02
    Curate evidence

    Each claim is entered with study context, identifiers, methods, results, and quality notes.

  3. 03
    Normalise

    Gene, trait, stress, assembly, tissue, and growth-stage terms are mapped to controlled records.

  4. 04
    Score and review

    Two passes apply the evidence rubric and resolve uncertain or conflicting claims.

  5. 05
    Explore candidates

    The interface compares evidence strength, directness, species, conditions, and linked orthologues.

Demonstration scenario

A user searches for drought-related evidence in rice and millet. The explorer separates directly validated genes from expression-only and orthology-inferred candidates, displays chromosome locations and study conditions, and traces each statement to the public source and curator score.

Engineering

Technical architecture

Web application
Nuxt and Vue for curation forms, search, filters, networks, genomic locations, and study comparison.
Evidence API
FastAPI for controlled terms, genes, studies, evidence records, scores, links, and exports.
Data layer
PostgreSQL for crops, assemblies, genes, traits, stresses, studies, evidence, and curation history.
Biological processing
Python and Biopython for sequence identifiers, coordinates, homologues, validation, and import adapters.
Search layer
PostgreSQL search or Elasticsearch for structured gene, trait, crop, condition, and evidence queries.

Testing

Evaluation

Evaluation measures

  • Identifier and coordinate mapping accuracy on prepared reference records
  • Inter-curator agreement for evidence categories and scores
  • Precision of gene, trait, crop, and stress search results
  • Correct separation of direct, association, expression, and inferred evidence
  • Traceability from every displayed claim to source and curation decision
  • Import, search, network, and comparison response time across record volumes

System boundaries

  • The explorer summarises public evidence and does not design gene edits, transformation experiments, or release strategies.
  • A linked gene is not proof of a useful field phenotype in another variety, crop, or environment.
  • Breeding, genetic modification, genome editing, biosafety, and field decisions require qualified institutions and regulatory approval.
  • Copyrighted sources are represented through citation and structured summaries, not copied full text.

Included

  1. 01Gene, crop, trait, study, and evidence interface
  2. 02Curation, normalisation, orthology, and evidence-scoring modules
  3. 03Evidence tables, networks, chromosome views, and comparison tools
  4. 04Prepared public gene and study records with validation results
  5. 05Complete source code in a private GitHub repository
  6. 06Complete project documentation with synopsis, abstract, methodology, biological data-flow diagrams, analysis results, screenshots, and conclusion
  7. 07Setup and usage guide

Project record

No buyer information is collected on this page.

Permanent project ID
GP-BT-1BQK7YK
Catalogued
21 Aug 2026
Completed
Pending
Verified
Pending
Demonstration
Added when ready

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.