TAILIEUCHUNG - Báo cáo khoa học: "Extracting Regulatory Gene Expression Networks from PubMed"

We present an approach using syntactosemantic rules for the extraction of relational information from biomedical abstracts. The results show that by overcoming the hurdle of technical terminology, high precision results can be achieved. From abstracts related to baker’s yeast, we manage to extract a regulatory network comprised of 441 pairwise relations from 58,664 abstracts with an accuracy of 83–90%. To achieve this, we made use of a resource of gene/protein names considerably larger than those used in most other biology related information extraction approaches. . | Extracting Regulatory Gene Expression Networks from PubMed Jasmin Saric EML Research gGmbH Heidelberg Germany saric@ Lars J. Jensen EMBL Heidelberg Germany jensen@ Rossitza Ouzounova EMBL Heidelberg Germany ouzounov@ Isabel Rojas EML Research gGmbH Heidelberg Germany rojas@ Abstract We present an approach using syntacto-semantic rules for the extraction of relational information from biomedical abstracts. The results show that by overcoming the hurdle of technical terminology high precision results can be achieved. From abstracts related to baker s yeast we manage to extract a regulatory network comprised of 441 pairwise relations from 58 664 abstracts with an accuracy of 83-90 . To achieve this we made use of a resource of gene protein names considerably larger than those used in most other biology related information extraction approaches. This list of names was included in the lexicon of our retrained part-of-speech tagger for use on molecular biology abstracts. For the domain in question an accuracy of was attained on POS-tags. The method is easily adapted to other organisms than yeast allowing us to extract many more biologically relevant relations. 1 Introduction and related work A massive amount of information is buried in scientific publications more than 500 000 publications per year . Therefore the need for information extraction IE and text mining in the life sciences is drastically increasing. Most of the ongoing work is being dedicated to deal with Peer Bork EMBL Heidelberg Germany bork@ PubMed1 abstracts. The technical terminology of biomedicine presents the main challenge of applying IE to such a corpus Hobbs 2003 . The goal of our work is to extract from biological abstracts which proteins are responsible for regulating the expression . transcription or translation of which genes. This means to extract a specific type of pairwise relations between biological entities. This differs from the .

• Báo cáo khoa học
• Extracting Regulatory
• Gene Expression Networks
• PubMed
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học