• Genomics & Informatics
• /
• v.7 no.4
• /
• pp.212-216
• /
• 2009

WebChemDB is an integrated chemical database retrieval system that provides access to over 8 million publicly available chemical structures, including related information on their biological activities and direct links to other public chemical resources, such as PubChem, ChEBI, and DrugBank. The data are publicly available over the web, using two-dimensional (2D) and three-dimensional (3D) structure retrieval systems with various filters and molecular descriptors. The web services API also provides researchers with functionalities to programmatically manipulate, search, and analyze the data.

• Journal of Information Management
• /
• v.40 no.1
• /
• pp.217-234
• /
• 2009

In computer-based virtual lab, a bioscience researcher who wants to obtain bio information first uses a biodiversity-related database to retrieve information on species, ecology and distribution of an organism. The researcher also needs to access gene/protein databases such as GenBank or PDB to find information on the organism's genetic sequence and protein structure. Furthermore, the researcher should search for academic papers containing the information on the organism so that his research is based on comprehensive and accurate information. This series of activities often undermines research efficiency as it takes a lot of time and causes inconvenience on the part of researchers. To solve such inconvenience, we analyzed various methods for integrated search and chosen schema integration. In addition, we analyzed each databases and extracted metadata for designing schema integration. This paper introduces a biological information retrieval system(BIRS) using schema integration and it's interface that will increase research efficiency for bioscience.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2007.02a
• /
• pp.48-52
• /
• 2007

As huge amount of literature including biological data is being generated after post genome era, it becomes difficult for researcher to find useful knowledge from the biological databases. Bio-text mining and related natural language processing technique are the key issues in the intelligent knowledge retrieval from the biological databases. We propose a bio-text mining technique for the biologists who find Knowledge from the huge literature. At first, web robot is used to extract and transform related literature from remote databases. To improve retrieval speed, we generate an inverted file for keywords in the literature. Then, text mining system is used for extracting given knowledge patterns and keywords. Finally, we construct a grid computing environment to guarantee processing speed in the text mining even for huge literature databases. In the real experiment for 10,000 bio-literatures, the system shows 95% precision and 98% recall.

• Journal of Information Science Theory and Practice
• /
• v.2 no.1
• /
• pp.6-21
• /
• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.

• The KIPS Transactions:PartD
• /
• v.11D no.4
• /
• pp.755-764
• /
• 2004

Recently, the rapid development of biotechnology brings the explosion of biological data and biological data host. Moreover, these data are highly distributed and heterogeneous, reflecting the distribution and heterogeneity of the Molecular Biology research community. As a consequence, the integration and interoperability of molecular biology databases are issue of considerable importance. But, up to now, most of the integrated systems such as link based system, data warehouse based system have many problems which are keeping the data up to date when the schema and data of the data source are changed. For this reason, the integrated system using web service technology that allow biological data to be fully exploited have been proposed. In this paper, we built the integrated system if the bio sequence information bated on the web service technology. The developed system allows users to get data with many format such as BSML, GenBank, Fasta to traverse disparate data resources. Also, it has better retrieval performance because the retrieval modules of the external database proceed in parallel.

• Bioinformatics and Biosystems
• /
• v.1 no.1
• /
• pp.46-50
• /
• 2006

According to the advancement of experimental techniques in molecular biology, genomic and protein sequence databases are increasing in size exponentially, and mean sequence lengths are also increasing. Because the sizes of these databases become larger, it is difficult to search similar sequences in biological databases with significant homologies to a query sequence. In this paper, we present the N-gram indexing method to retrieve similar sequences fast, precisely and comparably. This method regards a protein sequence as a text written in language of 20 amino acid codes, adapts N-gram tokens of fixed-length as its indexing scheme for sequence strings. After such tokens are indexed for all the sequences in the database, sequences can be searched with information retrieval algorithms. Using this new method, we have developed a protein sequence search system named as ProSeS (PROtein Sequence Search). ProSeS is a protein sequence analysis system which provides overall analysis results such as similar sequences with significant homologies, predicted subcellular locations of the query sequence, and major keywords extracted from annotations of similar sequences. We show experimentally that the N-gram indexing approach saves the retrieval time significantly, and that it is as accurate as current popular search tool BLAST.

• ETRI Journal
• /
• v.37 no.4
• /
• pp.813-823
• /
• 2015

Because protein is a primary element responsible for biological or biochemical roles in living bodies, protein function is the core and basis information for biomedical studies. However, recent advances in bio technologies have created an explosive increase in the amount of published literature; therefore, biomedical researchers have a hard time finding needed protein function information. In this paper, a classification system for biomedical literature providing protein function evidence is proposed. Note that, despite our best efforts, we have been unable to find previous studies on the proposed issue. To classify papers based on protein function evidence, we should consider whether the main claim of a paper is to assert a protein function. We, therefore, propose two novel features - protein and assertion. Our experimental results show a classification performance with 71.89% precision, 90.0% recall, and a 79.94% F-measure. In addition, to verify the usefulness of the proposed classification system, two case study applications are investigated - information retrieval for protein function and automatic summarization for protein function text. It is shown that the proposed classification system can be successfully applied to these applications.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.5
• /
• pp.990-995
• /
• 2010

Harris corner detector is commonly used to detect feature points for recognizing 2-D or 3-D objects. However, the feature points calculated from both of query and target objects need to be same positions to guarantee accurate recognitions. In order to check the positions of calculated feature points, we generate a Huffman tree which is based on adjacent feature values as inputs. However, the structures of two Huffman trees will be same as long as both of a query and targets have same feature values no matter how different their positions are. In this paper, we sort feature values and calculate the Euclidean distances of coordinates between two adjacent feature values. The Huffman Tree is generated with these Euclidean distances. As a result, the information of point locations can be included in the generated Huffman tree. This is the main strategy for accurate recognitions. We call this system as the HRM(Hybrid Retrieval Machine). This system works very well even when artificial random noises are added to original data. HRM can be used to recognize biological data such as proteins, and it will curtail the costs which are required to biological experiments.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2000.04a
• /
• pp.311-314
• /
• 2000

분자 생물학의 발전염기서열, 단백질 서열, 지놈 서열 등의 서열데이터베이스와 단백질 3차구조를 제공하는 구조 데이터베이스등이 구축되어서 웹을 통해 많은 정보를 제공하고 있다. 전세계적으로 분산되어 있는 다양한 생물정보 데이터베이스의 효율적인 검색을 위해서 통합 검색 시스템의 개발이 필요하다. 이 논문에서는 전세계의 생물정보 데이터베이스의 개발 현황을 보이고 분산되어 있는 생물정보데이터베이스로부터 통합검색을 위한 생물정보 통합검색시스템(GenPlus)를 제안하였다. 제안한 GenPlus 에서는 염기 서열, 단백질서열, 그리고 키워드를 이용한 서열정보, 구조정보,완전한 지놈 정보, 그리고 문헌정보의 통합 검색을 제공한다.

• Journal of KIISE:Databases
• /
• v.32 no.1
• /
• pp.24-42
• /
• 2005

Characteristics of biological data including genome sequences are heterogeneous and various. Although the need of management systems for genome sequencing which should reflect biological characteristics has been raised, most current biological databases provide restricted function as repositories for biological data. Therefore, this paper describes a management system of nucleotide sequences at the level of biological laboratories. It includes format transformation, editing, storing and retrieval for collected nucleotide sequences from public databases, and handles sequence produced by experiments. It uses BSML based on XML as a common format in order to extract data fields and transfer heterogeneous sequence formats. To manage sequences and their changes, version management system for originated DNA is required so as to detect transformed new sequencing appearance and trigger database update. Our experimental results show that applying active trigger rules to manage changes of sequences can automatically store changes of sequences into databases.