Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0024
M. Hayashida, T. Akutsu
This paper proposes series of methods for measuring the similarity of protein structures. In the proposed methods, an original protein structure is transformed into a distance matrix, which is regarded as a two-dimensional image. Then, the similarity of two protein structures is measured by a kind of compression ratio of the concatenated image. We employed several image compression algorithms: JPEG, GIF, PNG, IFS, and SPC, and audio compression algorithms: MP3 and FLAC. We applied the proposed method to clustering of protein structures. The results of computational experiments suggest that SPC has the best performance.
{"title":"Image Compression-based Approach to Measuring the Similarity of Protein Structures","authors":"M. Hayashida, T. Akutsu","doi":"10.1142/9781848161092_0024","DOIUrl":"https://doi.org/10.1142/9781848161092_0024","url":null,"abstract":"This paper proposes series of methods for measuring the similarity of protein structures. In the proposed methods, an original protein structure is transformed into a distance matrix, which is regarded as a two-dimensional image. Then, the similarity of two protein structures is measured by a kind of compression ratio of the concatenated image. We employed several image compression algorithms: JPEG, GIF, PNG, IFS, and SPC, and audio compression algorithms: MP3 and FLAC. We applied the proposed method to clustering of protein structures. The results of computational experiments suggest that SPC has the best performance.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"31 1","pages":"221-230"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73481435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0030
Xingming Zhao, Rui-Sheng Wang, Luonan Chen, K. Aihara
This paper presents a novel method for recovering signaling pathways from protein-protein interaction networks automatically. Given an undirected weighted protein interaction network, finding signaling pathways is treated as searching for the optimal subnetworks from the network according to some cost function. To approach this optimum problem, an integer linear programming model is proposed in this work to model the signal pathways from the protein interaction network. The numerical results on three known yeast MAPK signal pathways demonstrate the effic iency and effectiveness of the proposed method.
{"title":"Automatic Modeling of Signal Pathways from Protein-Protein Interaction Networks","authors":"Xingming Zhao, Rui-Sheng Wang, Luonan Chen, K. Aihara","doi":"10.1142/9781848161092_0030","DOIUrl":"https://doi.org/10.1142/9781848161092_0030","url":null,"abstract":"This paper presents a novel method for recovering signaling pathways from protein-protein interaction networks automatically. Given an undirected weighted protein interaction network, finding signaling pathways is treated as searching for the optimal subnetworks from the network according to some cost function. To approach this optimum problem, an integer linear programming model is proposed in this work to model the signal pathways from the protein interaction network. The numerical results on three known yeast MAPK signal pathways demonstrate the effic iency and effectiveness of the proposed method.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"18 1","pages":"287-296"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77875436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0015
Jialiang Yang, Louxin Zhang
Transition seeds exhibit a good tradeofi between sensitivity and speciflcity for homology search in both coding and non-coding regions. But, identifying good transition seeds is extremely hard. We study the hit probability of high-order seed patterns. Based on our theoretical results, we propose an e‐cient method for ranking transition seeds for seed design.
{"title":"Run Probability of High-Order Seed Patterns and its Applications to Finding Good Transition Seeds","authors":"Jialiang Yang, Louxin Zhang","doi":"10.1142/9781848161092_0015","DOIUrl":"https://doi.org/10.1142/9781848161092_0015","url":null,"abstract":"Transition seeds exhibit a good tradeofi between sensitivity and speciflcity for homology search in both coding and non-coding regions. But, identifying good transition seeds is extremely hard. We study the hit probability of high-order seed patterns. Based on our theoretical results, we propose an e‐cient method for ranking transition seeds for seed design.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"57 1","pages":"123-132"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75901877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0010
Suryani Lukman, Kelvin Sim, Jinyan Li, Y. Chen
To assess the physico-chemical characteristics of protein-protein interactions, protein sequences and overall structural folds have been analyzed previously. To highlight this, discovery and examination of amino acid patterns at the binding sites defined by structural proximity in 3-dimensional (3D) space are essential. In this paper, we investigate the interacting preferences of 3D pattern pairs discovered separately in transient and obligate protein complexes. These 3D pattern pairs are not necessarily sequence-consecutive, but each residue in two groups of amino acids from two proteins in a complex is within certain °A threshold to most residues in the other group. We develop an algorithm called AA-pairs by which every pair of interacting proteins is represented as a bipartite graph, and it discovers all maximal quasi-bicliques from every bipartite graph to form our 3D pattern pairs. From 112 and 2533 highly conserved 3D pattern pairs discovered in the transient and obligate complexes respectively, we observe that Ala and Leu is the highest occuring amino acid in interacting 3D patterns of transient (20.91%) and obligate (33.82%) complexes respectively. From the study on the dipeptide composition on each side of interacting 3D pattern pairs, dipeptides Ala-Ala and Ala-Leu are popular in 3D patterns of both transient and obligate complexes. The interactions between amino acids with large hydrophobicity difference are present more in the transient than in the obligate complexes. On contrary, in obligate complexes, interactions between hydrophobic residues account for the top 5 most occuring amino acid pairings.
{"title":"Interacting Amino Acid Preferences of 3D Pattern Pairs at the Binding Sites of Transient and Obligate Protein Complexes","authors":"Suryani Lukman, Kelvin Sim, Jinyan Li, Y. Chen","doi":"10.1142/9781848161092_0010","DOIUrl":"https://doi.org/10.1142/9781848161092_0010","url":null,"abstract":"To assess the physico-chemical characteristics of protein-protein interactions, protein sequences and overall structural folds have been analyzed previously. To highlight this, discovery and examination of amino acid patterns at the binding sites defined by structural proximity in 3-dimensional (3D) space are essential. In this paper, we investigate the interacting preferences of 3D pattern pairs discovered separately in transient and obligate protein complexes. These 3D pattern pairs are not necessarily sequence-consecutive, but each residue in two groups of amino acids from two proteins in a complex is within certain °A threshold to most residues in the other group. We develop an algorithm called AA-pairs by which every pair of interacting proteins is represented as a bipartite graph, and it discovers all maximal quasi-bicliques from every bipartite graph to form our 3D pattern pairs. From 112 and 2533 highly conserved 3D pattern pairs discovered in the transient and obligate complexes respectively, we observe that Ala and Leu is the highest occuring amino acid in interacting 3D patterns of transient (20.91%) and obligate (33.82%) complexes respectively. From the study on the dipeptide composition on each side of interacting 3D pattern pairs, dipeptides Ala-Ala and Ala-Leu are popular in 3D patterns of both transient and obligate complexes. The interactions between amino acids with large hydrophobicity difference are present more in the transient than in the obligate complexes. On contrary, in obligate complexes, interactions between hydrophobic residues account for the top 5 most occuring amino acid pairings.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"185 1","pages":"69-78"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73943024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0021
Jiayu Wen, B. Parker, G. Weiller
Many RNA functions are determined by their specific secondary and tertiary structures. These structures are folded by the canonical G::C and A::U base pairings as well as by the non-canonical G::U complementary bases. G::U base pairings in RNA secondary structures may induce structural asymmetries between the transcribed and non-transcribed strands in their corresponding DNA sequences. This is likely so because the corresponding C::A nucleotides of the complementary strand do not pair. As a consequence, the secondary structures that form from a genomic sequence depend on the strand transcribed. We explore this idea to investigate the size and significance of both global and local secondary structure formation differentials in several non-coding RNA families and mRNAs. We show that both thermodynamic stability of global RNA structures in the transcribed strand and RNA structure strand asymmetry are statistically stronger than that in randomized versions preserving the same di-nucleotide base composition and length, and is especially pronounced in microRNA precursors. We further show that a measure of local structural strand asymmetry within a fixed window size, as could be used in detecting and characterizing transcribed regions in a full genome scan, can be used to predict the transcribed strand across ncRNA families.
{"title":"Analysis of Structural Strand Asymmetry in Non-coding RNAs","authors":"Jiayu Wen, B. Parker, G. Weiller","doi":"10.1142/9781848161092_0021","DOIUrl":"https://doi.org/10.1142/9781848161092_0021","url":null,"abstract":"Many RNA functions are determined by their specific secondary and tertiary structures. These structures are folded by the canonical G::C and A::U base pairings as well as by the non-canonical G::U complementary bases. G::U base pairings in RNA secondary structures may induce structural asymmetries between the transcribed and non-transcribed strands in their corresponding DNA sequences. This is likely so because the corresponding C::A nucleotides of the complementary strand do not pair. As a consequence, the secondary structures that form from a genomic sequence depend on the strand transcribed. We explore this idea to investigate the size and significance of both global and local secondary structure formation differentials in several non-coding RNA families and mRNAs. We show that both thermodynamic stability of global RNA structures in the transcribed strand and RNA structure strand asymmetry are statistically stronger than that in randomized versions preserving the same di-nucleotide base composition and length, and is especially pronounced in microRNA precursors. We further show that a measure of local structural strand asymmetry within a fixed window size, as could be used in detecting and characterizing transcribed regions in a full genome scan, can be used to predict the transcribed strand across ncRNA families.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"76 1","pages":"187-198"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86616444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Phylogenetic Reconstruction from Complete Gene Orders of Whole Genomes","authors":"K. M. Swenson, W. Arndt, Jijun Tang, Bernard M. E. Moret","doi":"10.1142/9781848161092_0026","DOIUrl":"https://doi.org/10.1142/9781848161092_0026","url":null,"abstract":"Reference LCBB-CONF-2007-003 URL: http://sunflower.kuicr.kyoto-u.ac.jp/apbc2008/ Record created on 2007-10-13, modified on 2017-05-12","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"14 1","pages":"241-250"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86742389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0023
Sebastian Böcker, Sebastian Briesemeister, Quang Bao Anh Bui, A. Truß
Clustering objects with respect to a given similarity or distance measure is a problem often encountered in computational biology. Several well-known clustering algorithms are based on transforming the input matrix into a weighted graph although the resulting WEIGHTED CLUSTER EDITING problem is computationally hard: here, we transform the input graph into a disjoint union of cliques such that the sum of weights of all modified edges is minimized. We present fixed-parameter algorithms for this problem which guarantee to find an optimal solution in provable worst-case running time. We introduce a new data reduction operation (merging vertices) that has no counterpart in the unweighted case and strongly cuts down running times in practice. We have applied our algorithms to both artificial and biological data. Despite the complexity of the problem, our method often allows exact computation of optimal solutions in reasonable running time.
{"title":"A Fixed-Parameter Approach for Weighted Cluster Editing","authors":"Sebastian Böcker, Sebastian Briesemeister, Quang Bao Anh Bui, A. Truß","doi":"10.1142/9781848161092_0023","DOIUrl":"https://doi.org/10.1142/9781848161092_0023","url":null,"abstract":"Clustering objects with respect to a given similarity or distance measure is a problem often encountered in computational biology. Several well-known clustering algorithms are based on transforming the input matrix into a weighted graph although the resulting WEIGHTED CLUSTER EDITING problem is computationally hard: here, we transform the input graph into a disjoint union of cliques such that the sum of weights of all modified edges is minimized. We present fixed-parameter algorithms for this problem which guarantee to find an optimal solution in provable worst-case running time. We introduce a new data reduction operation (merging vertices) that has no counterpart in the unweighted case and strongly cuts down running times in practice. We have applied our algorithms to both artificial and biological data. Despite the complexity of the problem, our method often allows exact computation of optimal solutions in reasonable running time.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"35 1","pages":"211-220"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89978677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0029
Yunlei Li, D. Ridder, M. D. Groot, M. Reinders
We introduce a comparative analysis of metabolic reaction networks between different species. Our method systematically investigates full metabolic networks of multiple species at the same time, with the goal of identifying highly similar yet non-identical pathways which execute the same metabolic function, i.e. the transformation of a specific substrate into a certain end product via similar reactions. We present a clear framework for matching metabolic pathways, and propose a scoring scheme which combines enzyme functional similarity with protein sequence similarity. This analysis helps to gain insight in the biological differences between species and provides comprehensive information on diversity in pathways between species and alternative pathways within species, which is useful for pharmaceutical and industrial bioengineering targets. The results also generate hypotheses for improving current metabolic networks or constructing such networks for currently unannotated species.
{"title":"Metabolic Pathway Alignment (M-Pal) Reveals Diversity and Alternatives in Conserved Networks","authors":"Yunlei Li, D. Ridder, M. D. Groot, M. Reinders","doi":"10.1142/9781848161092_0029","DOIUrl":"https://doi.org/10.1142/9781848161092_0029","url":null,"abstract":"We introduce a comparative analysis of metabolic reaction networks between different species. Our method systematically investigates full metabolic networks of multiple species at the same time, with the goal of identifying highly similar yet non-identical pathways which execute the same metabolic function, i.e. the transformation of a specific substrate into a certain end product via similar reactions. We present a clear framework for matching metabolic pathways, and propose a scoring scheme which combines enzyme functional similarity with protein sequence similarity. This analysis helps to gain insight in the biological differences between species and provides comprehensive information on diversity in pathways between species and alternative pathways within species, which is useful for pharmaceutical and industrial bioengineering targets. The results also generate hypotheses for improving current metabolic networks or constructing such networks for currently unannotated species.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"474 1","pages":"273-286"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73901568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0008
Alireza Hadj Khodabakhshi, Ján Manuch, A. Rafiey, Arvind Gupta
divides amino acids to two groups: hydrophobic (H) and polar (P), and considers only hydrophobic interactions between neighboring H amino in the energy formula. Another significant force acting during the protein folding are sulfide (SS) bridges between two cysteine amino acids. In this paper, we will enrich the HP model by adding cysteines as the third group of amino acids. A cysteine monomer acts as an H amino acid, but in addition two neighboring cysteines can form a bridge to further reduce the energy of the fold. We call our model the HPC model. We consider a subclass of linear structures designed in Gupta et al. 1 which is rich enough to approximate (although more coarsely) any given structure. We refine the structures for the HPC model by setting approximately a half of H amino acids to cysteine ones. We conjecture that these structures are stable under the HPC model and prove it under an additional assumption that non-cysteine amino acids act as cysteine ones, i.e., they tend to form their own bridges to reduce the energy. In the proof we will make an efficient use of a computational tool 2DHPSolver which significantly speeds up the progress in the technical part of the proof. This is a preliminary work, and we believe that the same techniques can be used to prove this result without the artificial assumption about non-cysteine H monomers.
{"title":"Structure-Approximating Design of Stable Proteins in 2D HP Model Fortified by Cysteine Monomers","authors":"Alireza Hadj Khodabakhshi, Ján Manuch, A. Rafiey, Arvind Gupta","doi":"10.1142/9781848161092_0008","DOIUrl":"https://doi.org/10.1142/9781848161092_0008","url":null,"abstract":"divides amino acids to two groups: hydrophobic (H) and polar (P), and considers only hydrophobic interactions between neighboring H amino in the energy formula. Another significant force acting during the protein folding are sulfide (SS) bridges between two cysteine amino acids. In this paper, we will enrich the HP model by adding cysteines as the third group of amino acids. A cysteine monomer acts as an H amino acid, but in addition two neighboring cysteines can form a bridge to further reduce the energy of the fold. We call our model the HPC model. We consider a subclass of linear structures designed in Gupta et al. 1 which is rich enough to approximate (although more coarsely) any given structure. We refine the structures for the HPC model by setting approximately a half of H amino acids to cysteine ones. We conjecture that these structures are stable under the HPC model and prove it under an additional assumption that non-cysteine amino acids act as cysteine ones, i.e., they tend to form their own bridges to reduce the energy. In the proof we will make an efficient use of a computational tool 2DHPSolver which significantly speeds up the progress in the technical part of the proof. This is a preliminary work, and we believe that the same techniques can be used to prove this result without the artificial assumption about non-cysteine H monomers.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"40 1","pages":"49-58"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85231418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-12-01DOI: 10.1142/9781848161092_0002
M. Kanehisa
a suite of databases that integrates genomic, chemical, and systemic functional aspects of the biological systems. KEGG provides a reference knowledge base for linking genomes to life through the process of PATHWAY mapping, which is to map, for example, a genomic or transcriptomic content of genes to KEGG reference pathways to infer systemic behaviors of the cell or the organism. In addition, KEGG provides a reference knowledge base for linking genomes to the environment, such as for the analysis of drug-target relationships, through the process of BRITE mapping. KEGG BRITE is an ontology database representing functional hierarchies of various biological objects, including molecules, cells, organisms, diseases, and drugs, as well as relationships among them. The KEGG resource is being expanded to suit the needs for practical applications. KEGG PATHWAY now contains 26 pathway maps for human diseases in four subcategories: neurodegenerative disorders, infectious diseases, metabolic disorders, and cancers. Although such maps will continue to be added, they will never be sufficient to represent our knowledge of molecular mechanisms of diseases because in many cases it is too fragmentary to represent as pathways. KEGG DISEASE is a new addition to the KEGG suite accumulating molecular-level knowledge on diseases represented as lists of genes, drugs, biomarkers, etc. KEGG DRUG now covers all approved drugs in the U.S. and Japan. KEGG DRUG is a structure-based database. Each entry is a unique chemical structure that is linked to standard generic names, and is associated with efficacy and target information as well as drug classifications. Target information is presented in the context of KEGG pathways and drug classifications are part of KEGG BRITE. The generic names are linked to trade names and subsequently to outside resources of package insert information whenever available. This reflects our effort to make KEGG more useful to the general public.
{"title":"KEGG for Medical and Pharmaceutical Applications","authors":"M. Kanehisa","doi":"10.1142/9781848161092_0002","DOIUrl":"https://doi.org/10.1142/9781848161092_0002","url":null,"abstract":"a suite of databases that integrates genomic, chemical, and systemic functional aspects of the biological systems. KEGG provides a reference knowledge base for linking genomes to life through the process of PATHWAY mapping, which is to map, for example, a genomic or transcriptomic content of genes to KEGG reference pathways to infer systemic behaviors of the cell or the organism. In addition, KEGG provides a reference knowledge base for linking genomes to the environment, such as for the analysis of drug-target relationships, through the process of BRITE mapping. KEGG BRITE is an ontology database representing functional hierarchies of various biological objects, including molecules, cells, organisms, diseases, and drugs, as well as relationships among them. The KEGG resource is being expanded to suit the needs for practical applications. KEGG PATHWAY now contains 26 pathway maps for human diseases in four subcategories: neurodegenerative disorders, infectious diseases, metabolic disorders, and cancers. Although such maps will continue to be added, they will never be sufficient to represent our knowledge of molecular mechanisms of diseases because in many cases it is too fragmentary to represent as pathways. KEGG DISEASE is a new addition to the KEGG suite accumulating molecular-level knowledge on diseases represented as lists of genes, drugs, biomarkers, etc. KEGG DRUG now covers all approved drugs in the U.S. and Japan. KEGG DRUG is a structure-based database. Each entry is a unique chemical structure that is linked to standard generic names, and is associated with efficacy and target information as well as drug classifications. Target information is presented in the context of KEGG pathways and drug classifications are part of KEGG BRITE. The generic names are linked to trade names and subsequently to outside resources of package insert information whenever available. This reflects our effort to make KEGG more useful to the general public.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"42 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80670195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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