유전체 정보 연계 시스템 Genome InfraNet

분석 프로그램 검색

Study : 1711058371

연구과제 정보

accession,
2014M3C9A3064706
1711058371
유전자-주석-질병간 연관성 분석을 위한 문헌 데이터 마이닝 기술 개발
과학기술정보통신부
한국전자통신연구원
박수준
2020
2017-08-01 ~ 2018-05-31
권동섭
dongseop@gmail.com
01097837880

등록 프로그램 / 파이프라인 / 웹 서비스 정보

accession,

1. 분석 프로그램   2. 대용량 유전체 분석

한글명칭 EZ태그
영문명칭
프로그램 ezTag.zip
매뉴얼 program_manual_sample.xlsx
모식도 프로그램 전체 모식도 없음
웹 서비스 주소 https://eztag.bioqrator.org/
주요 내용 특징 Recently, advanced text-mining techniques have been shown to speed up manual data curation by providing human annotators with automated pre-annotations generated by rules or machine learning models. Due to the limited training data available, however, current annotation systems primarily focus only on common concept types such as genes or diseases. To support annotating a wide variety of biological concepts with or without pre-existing training data, we developed ezTag, a web-based annotation tool that allows curators to perform annotation and provide training data with humans in the loop. ezTag supports both abstracts in PubMed and full-text articles in PubMed Central. It also provides lexicon-based concept tagging as well as the state-of-the-art pre-trained taggers such as TaggerOne, GNormPlus, and tmVar
주요 기능 1. ezTag supports all PubMed abstracts and PMC open access articles. 2. ezTag users have multiple ways of annotating bio-entities. 3. ezTag explicitly supports training and annotating text iteratively. 4. Other features include a user-friendly interface based on PubTator user feedback, automatic session ID-based login.
사용방법 1. You need to install git, ruby, rails, and MySQL first. 2. Clone this repository : https://github.com/ncbi-nlp/ezTag.git 3. cd ezTag 4. bundle install 5. You need to create your own 'database.yml' and 'secrets.yml' in 'config' directory. You may refer sample files in the config directory. 6. rake db:create 7. rake db:migrate 8. rails s
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기타
Git, Rails, MySQL, Ruby