Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

GECKB

General information

URL: https://zenodo.org/record/7577127
Full name: Gene Expression-Cancer Knowledge Base
Description: Gene Expression-Cancer Knowledge Base focuses on precision medicine and build the largest KB on 'fine-grained' gene expression-cancer associations-a key to complement and validate experimental data for cancer research
Year founded: 2023
Last update: 2024-07-18
Version: v1.0
Accessibility:
Accessible
Country/Region: Italy

Classification & Tag

Data type:
Data object:
Animal
NA
Database category:
Major species:
Keywords:

Contact information

University/Institution: University of Padova
Address: Department of Information Engineering, University of Padova, Via G. Gradenigo 6b, Padova 35131, Italy
City:
Province/State: Padova
Country/Region: Italy
Contact name (PI/Team): Stefano Marchesin
Contact email (PI/Helpdesk): stefano.marchesin@unipd.it

Publications

37768281
Building a large gene expression-cancer knowledge base with limited human annotations. [PMID: 37768281]
Stefano Marchesin, Laura Menotti, Fabio Giachelle, Gianmaria Silvello, Omar Alonso

Cancer prevention is one of the most pressing challenges that public health needs to face. In this regard, data-driven research is central to assist medical solutions targeting cancer. To fully harness the power of data-driven research, it is imperative to have well-organized machine-readable facts into a knowledge base (KB). Motivated by this urgent need, we introduce the Collaborative Oriented Relation Extraction (CORE) system for building KBs with limited manual annotations. CORE is based on the combination of distant supervision and active learning paradigms and offers a seamless, transparent, modular architecture equipped for large-scale processing. We focus on precision medicine and build the largest KB on 'fine-grained' gene expression-cancer associations-a key to complement and validate experimental data for cancer research. We show the robustness of CORE and discuss the usefulness of the provided KB. Database URL https://zenodo.org/record/7577127.

Database (Oxford). 2023:2023() | 2 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
5308/6895 (23.031%)
Health and medicine:
1335/1738 (23.245%)
Expression:
1075/1347 (20.267%)
5308
Total Rank
2
Citations
1
z-index

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Record metadata

Created on: 2024-07-15
Curated by:
Wenzhuo Cheng [2024-08-22]
Miaomiao Wang [2024-07-19]
shaosen zhang [2024-07-15]