AGAC Portal

, “Annotation of Genes with Alteration-Centric function changes”. — A customized corpus for mining functions caused by mutations.

undefined We are listing all about AGAC in this portal: Corpus annotation idea, data info, data usage in AGAC track as a shared task, baseline Python codes for AGAC track, and downstream applications with AGAC.

undefined 在这个页面中，我们列出了与AGAC语料库有关的标注规则、数据格式、代码和应用案例。

Toy Example

(标注规则)

AGAC annotates the following labels in biomedical texts, aiming to describe the downstream molecular/cellular physiological mechanism after a gain/loss-of-function mutation.

Annotation Task 1. NER with the following labels:

Variation (突变)
Molecular physiological function (分子功能)
Interaction (互作)
Pathway (通路)
Cellular physiological function (细胞功能)
Positive regulation (正调控)
Negative regulation (负调控)
Regulation (调控)
Protein/Gene (蛋白/基因)

Annotation Task 2. Thematic role with the following:

Theme of (主事)
Cause of (致事)

Corpus Guideline Book

(标注指南)

Guideline of AGAC trigger words design follows the central dogma and fundamental functioning procedure of molecular biology.

The annotation guideline is released via the following publication.

Ref: Yuxing Wang, et. al. Guideline Design of an Active Gene Annotation Corpus for the Purpose of Drug Repurposing. 2018 11th CISP-BMEI 2018, Oct, 2018, Beijing.

Corpus Development

(标注历史)

The corpus construction got started at Sep, 2017, and reached its latest version in 2019 when it was released as the training data in AGAC Track in BioNLP-OST, 2019.

1) AGAC (v1.0). (Sep, 2017—Aug,2018)
2) AGAC (v1.1). (Sep, 2018—Jan,2019)
3) AGAC (V2.0). (Feb, 2019 —Aug, 2019)

Ref:

Kaiyin Zhou, et al. GOF/LOF Knowledge Inference with Tensor Decomposition in Support of High order Link Discovery for Gene, MBE, 2019, 16(3):1376-1391.

Mina Gachloo, et al. A Review of the Drug Knowledge Discovery by Using BioNLP and Tensor or Matrix Decomposition. Genomics & Informatics, 2019, 17(2): e18.

Yuxing Wang, et al. An Active Gene Annotation Corpus and Its Application on Anti-epilepsy Drug Discovery. BIBM 2019: International Conference on Bioinformatics & Biomedicine, San Diego, U.S, Nov, 2019.

Corpus Availability and BioNLP Open Shared Task

(数据和开放共享任务)

The AGAC corpus is stored in PubAnnotation repo:

http://pubannotation.org/collections/AGAC

The corpus served as the data for the AGAC track in BioNLP OST 2019.

https://sites.google.com/view/bionlp-ost19-agac-track

Ref: Yuxing Wang, Kaiyin Zhou, Mina Gachloo, Jingbo Xia*. An Overview of the Active Gene Annotation Corpus and the BioNLP OST 2019 AGAC Track Tasks. BioNLP Open Shared Task 2019, workshop in EMNLP-IJCNLP 2019, Hong Kong.

Data with Json form

(数据格式)

AGAC corpus is provided with a JSON form.

Data description: https://sites.google.com/view/bionlp-ost19-agac-track/description

Baseline Python Codes

(基线方法和代码)

The baseline python codes are released in Github:

Task 1 (NER) https://github.com/bionlp-hzau/BERT-CRF-for-BioNLP-OST2019-AGAC-Task1

Task 2 (Thematic role labeling, aka., shallow semantic parsing) https://github.com/bionlp-hzau/BERT-for-BioNLP-OST2019-AGAC-Task2

AGAC on Alzheimer’s Disease

(AGAC在老年痴呆症的应用)

https://hzaubionlp.com/agac-on-alzheimers-disease/

Ref: Kaiyin Zhou, Yuxing Wang, Kevin Bretonnel Cohen, Jin-Dong Kim, Xiaohang Ma, Zhixue Shen, Xiangyu Meng, Jingbo Xia. Bridging Heterogeneous Mutation Data to Enhance Disease-Gene Discovery. Briefing in Bioinformatics, 2021, doi: 10.1093/bib/bbab079.