Visualization for Digesting a High Volume of the Biomedical Literature

Lee, Chang-Su,Park, Jin-Ah,Park, Jong-C. Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.1

The paradigm in biology is currently changing from that of conducting hypothesis-driven individual experiments to that of utilizing the results of a massive data analysis with appropriate computational tools. We present LayMap, an implemented visualization system that helps the user to deal with a high volume of the biomedical literature such as MEDLINE, through the layered maps that are constructed on the results of an information extraction system. LayMap also utilizes filtering and granularity for an enhanced view of the results. Since a biomedical information extraction system gives rise to a focused and effective way of slicing up the data space, the combined use of LayMap with such an information extraction system can help the user to navigate the data space in a speedy and guided manner. As a case study, we have applied the system to datasets of journal abstracts on 'MAPK pathway' and 'bufalin' from MEDLINE. With the proposed visualization, we have successfully rediscovered pathway maps of a reasonable quality for ERK, p38 and JNK. Furthermore, with respect to bufalin, we were able to identify the potentially interesting relation between the Chinese medicine Chan su and apoptosis with a high level of detail.

A Target Protein for Potassium Isolespedezate, A Bioactive Metabolite Controlling Nyctinasty

Manabe, Yoshiyuki,Iwakura, Izumi,Mukai, Makoto,Ueda, Minoru Korean Society for Bioinformatics and Systems Biol 2009 Interdisciplinary Bio Central (IBC) Vol.1 No.4

Introduction: Leguminous plants open their leaves during the day and close them at night as if sleeping, a type of movement that follows circadian rhythms, and is known as nyctinastic movement. This phenomenon is controlled by two endogenous bioactive substances that exhibit opposing activities: Leaf-Opening Factor (LOF), which opens the leaves, and Leaf-Closing Factor (LCF), which closes them. Potassium isolespedezate (1) is LOF for Cassia obtusifolia and other species of the genus Cassia. We report on the detection and identification of the target proteins of 1 using the stepwise FLAG-tagging strategy. Materials and Methods: First, we labeled the target protein with azide group by incubating the iodoacetamide-type probe (2), which is the target cell of 1, and then, succeeded in introduction of FLAG using click chemistry. Results and Discussion: By using this method, the 83 kDa cytoplasmic protein (CTPL; cytosolic target protein of lespedezate 1) was detected and purified as a target protein of 1. This protein was identified as MetE (5-methyltetrahydropteroyltriglutamate ?homocysteinemethyltransferase). Conclusion and Prospects: We developed stepwise FLAG-tagging strategy for purification of target protein of bioactive substances. Our results suggested that our strategies have a possibility to detect the target protein of a bioactive natural product in a highly complex living system.

Proteomics Data Analysis using Representative Database

Kwon, Kyung-Hoon,Park, Gun-Wook,Kim, Jin-Young,Park, Young-Mok,Yoo, Jong-Shin Korean Society for Bioinformatics and Systems Biol 2007 Bioinformatics and Biosystems Vol.2 No.2

In the proteomics research using mass spectrometry, the protein database search gives the protein information from the peptide sequences that show the best match with the tandem mass spectra. The protein sequence database has been a powerful knowledgebase for this protein identification. However, as we accumulate the protein sequence information in the database, the database size gets to be huge. Now it becomes hard to consider all the protein sequences in the database search because it consumes much computing time. For the high-throughput analysis of the proteome, usually we have used the non-redundant refined database such as IPI human database of European Bioinformatics Institute. While the non-redundant database can supply the search result in high speed, it misses the variation of the protein sequences. In this study, we have concerned the proteomics data in the point of protein similarities and used the network analysis tool to build a new analysis method. This method will be able to save the computing time for the database search and keep the sequence variation to catch the modified peptides.

In Vivo Reporter Gene Imaging: Recent Progress of PET and Optical Imaging Approaches

Min, Jung-Joon Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.1

Recent progress in the development of non-invasive imaging technologies continues to strengthen the role of molecular imaging biological research. These tools have been validated recently in variety of research models, and have been shown to provide continuous quantitative monitoring of the location(s), magnitude, and time-variation of gene delivery and/or expression. This article reviews the use of radionuclide, magnetic resonance, and optical imaging technologies as they have been used in imaging gene delivery and gene expression for molecular imaging applications. The studies published to date demonstrate that noninvasive imaging tools will help to accelerate pre-clinical model validation as well as allow for clinical monitoring of human diseases.

Prediction Accuracy Evaluation of Domain and Domain Combination Based Prediction Methods for Protein-Protein Interaction

Han, Dong-Soo,Jang, Woo-Hyuk Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

This paper compares domain combination based protein-protein interaction prediction method with domain based protein-protein interaction method. The prediction accuracy and reliability of the methods are compared using the same prediction technique and interaction data. According to the comparison, domain combination based prediction method has showed superior prediction accuracy to domain based prediction method for protein pairs with fully overlapped domains with protein pairs in learning sets. When we consider that domain combination based method has the effects of assigning a weight to each domain interaction, it implies that we can improve the prediction accuracies of currently available domain or domain combination based protein interaction prediction methods further by developing more advanced weight assignment techniques. Several significant facts revealed from the comparative studies are also described in this paper.

CiNet: GUI based Literature analysis tool using citation information

Lee, Se-Jun,Lee, Kwang-H. Korean Society for Bioinformatics and Systems Biol 2007 Bioinformatics and Biosystems Vol.2 No.1

Scientific literature is the most reliable and comprehensive source of knowledge for scientific and biomedical information. Citation information in the literature is also reliable source for linking between literatures. We proposed CiNet, a graphic user interface based tool that extracts the trend of the research using citation information. We can navigate related literatures and extract keywords from the linked literature using this tool. These extracted keywords will be helpful to researchers who want to survey the information.

Local structural alignment and classification of TIM barrel domains

Keum, Chang-Won,Kim, Ji-Hong,Jung, Jong-Sun Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

TIM barrel domain is widely studied since it is one of most common structure and mediates diverse function maintaining overall structure. TIM barrel domain's function is determined by local structural environment at the C-terminal end of barrel structure. We classified TIM barrel domains by local structural alignment tool, LSHEBA, to understand characteristics of TIM barrel domain's functionalvariation. TIM barrel domains classified as the same cluster share common structure, function and ligands. Over 80% of TIM barrels in clusters share exactly the same catalytic function. Comparing clustering result with that of SCOP, we found that it's important to know local structural environment of TIM barrel domains rather than overallstructure to understand specific structural detail of TIM barrel function. Non TIM barrel domains were associated to make different domain combination to form a different function. The relationship between domain combination, we suggested expected evolutional history. We finally analyzed the characteristics of amino acids around ligand interface.

Retrieving Protein Domain Encoding DNA Sequences Automatically Through Database Cross-referencing

Choi, Yoon-Sup,Yang, Jae-Seong,Ryu, Sung-Ho,Kim, Sang-Uk Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

Recent proteomic studies of protein domains require high-throughput and systematic approaches. Since most experiments using protein domains, the modules of protein-protein interactions, require gene cloning, the first experimental step should be retrieving DNA sequences of domain encoding regions from databases. For a large scale proteomic research, however, it is a laborious task to extract a large number of domain sequences manually from several inter-linked databases. We present a new methodology to retrieve DNA sequences of domain encoding regions through automatic database cross-referencing. To extract protein domain encoding regions, it traverses several inter-connected database with validation process. And we applied this method to retrieve all the EGF domain encoding DNA sequences of homo sapiens. This new algorithm was implemented using Python library PAMIE, which enables to cross-reference across distinct databases automatically.

Informatics for protein identification by tandem mass spectrometry; Focused on two most-widely applied algorithms, Mascot and SEQUEST

Sohn, Chang-Ho,Jung, Jin-Woo,Kang, Gum-Yong,Kim, Kwang-Pyo Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

Mass spectrometry (MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry (MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.

Protein Sequence Search based on N-gram Indexing

Hwang, Mi-Nyeong,Kim, Jin-Suk Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.1

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.