The metabolic pathway collection from EMP: the enzymes and metabolic pathways database.

The Enzymes and Metabolic Pathways database (EMP) is an encoding of the contents of over 10 000 original publications on the topics of enzymology and metabolism. This large body of information has been transformed into a queryable database. An extraction of over 1800 pictorial representations of metabolic pathways from this collection is freely available on the World Wide Web. We believe that this collection will play an important role in the interpretation of genetic sequence data, as well as offering a meaningful framework for the integration of many other forms of biological data.     

The metabolic pathway collection: an update.

The Metabolic Pathway Collection from EMP is an extraction of data from the larger Enzymes and Metabolic Pathways database (EMP). This extraction has been made publicly available in the hope that others will find it useful for a variety of purposes. The original release in October 1995 contained 1814 distinct pathways. The current collection contains 2180. Metabolic reconstructions for the first completely sequenced organisms-Haemophilus influenzae,Mycoplasma genitalium,Saccharomyces cerevisiaeandMethanococcus janaschii-are all included in the current release. All of the pathways in the collections are available as ASCII files in the form generated by the main curator, Evgeni Selkov. In addition, we are offering a more structured encoding of a subset of the collection; our initial release of this subcollection includes all of the pathways inMycoplasma genitalium, and we ultimately intend to offer the entire collection in this form as well.     

MDMPR:小鼠发育代谢表型库

小鼠发育代谢表型库(Mouse Developmental and Metabolic Phenotype Repository,MDMPR)是一个致力于小鼠资源和表型数据实时共享的开放性平台,它依托于科技部重点研发计划“发育编程及其代谢调节”专项项目“建立小鼠发育代谢表型库”。该项目预计在5年内完成500个发育代谢相关小鼠敲除模型的建立,并对其表型数据进行标准化的解析、建立表型数据库。MDMPR作为一个资源及数据集成的库,由多个子系统作为支撑,包括ES细胞数据库、项目管理系统、繁育管理系统、精子库管理系统、表型分析系统,信息化管理深入到项目中每个环节,从基因突变ES细胞制备、基因突变小鼠制备、小鼠繁育,精子冻存到最终的表型分析、数据处理及展示,保证了MDMPR产生数据的真实性及实时性。MDMPR除了不断地推进项目进行,增加自身产生的数据外,也在积极的整合其他的资源及数据,如人特异性基因敲除ES细胞库、蛋白相互作用数据库(STRING)、核心转录调节环路(dbCoRc)和Enhancer-Indel数据库,今后还将进一步整合,帮助发育代谢及其他领域的研究人员能够一站式的获取所需资源和数据、加快研究进程,最终服务于全人类的医疗事业。     

Entamoeba histolytica: construction and applications of subgenomic databases

Knowledge about the influence of environmental stress such as the action of chemotherapeutic agents on gene expression in Entamoeba histolytica is limited. We plan to use oligonucleotide microarray hybridization to approach these questions. As the basis for our array, sequence data from the genome project carried out by the Institute for Genomic Research (TIGR) and the Sanger Institute were used to annotate parts of the parasite genome. Three subgenomic databases containing enzymes, cytoskeleton genes, and stress genes were compiled with the help of the ExPASy proteomics website and the BLAST servers at the two genome project sites. The known sequences from reference species, mostly human and Escherichia coli, were searched against TIGR and Sanger E. histolytica sequence contigs and the homologs were copied into a Microsoft Access database. In a similar way, two additional databases of cytoskeletal genes and stress genes were generated. Metabolic pathways could be assembled from our enzyme database, but sometimes they were incomplete as is the case for the sterol biosynthesis pathway. The raw databases contained a significant number of duplicate entries which were merged to obtain curated non-redundant databases. This procedure revealed that some E. histolytica genes may have several putative functions. Representative examples such as the case of the delta-aminolevulinate synthase/serine palmitoyltransferase are discussed.     

Advances in growth hormone therapy: a new registry tool

Growth hormone (GH) deficiency is a rare condition, and physicians may lack clinical experience of its treatment. Despite evidence for the efficacy and tolerability of GH therapy, a substantial proportion of patients remain untreated. Registries and other large-scale databases are an important tool for expanding the evidence base for GH treatment. Since the mid-1980s, registries have provided data on important aspects of the safety and efficacy of GH treatment. Registries have also allowed pooling of data from patients with rare conditions that could otherwise not be recruited in sufficient numbers for clinical trials. Importantly for patients and their relatives, use of registry data has allowed the development of prediction models that indicate the likely outcomes of treatment. MEGHA (Metabolic Endocrinology and Growth Hormone Assessment) is a recently developed, observational database with a number of features not found in existing registries, including its use as a day-to-day clinical management tool, the ability to create individual sub-studies, direct comparison of personal data against the full database, and a particular focus on the transition from childhood to adulthood. This creative registry is a promising instrument for further research into GH-related disorders that will improve GH therapy and thus provide benefits for patients.     

Clustering Analysis of a Colombian Toxicological Database

The database analysis allows the return of experience needed to support decision-making processes in risk management. A Colombian toxicological database (TED) developed and maintained by the Center of Safety Information and Chemical Products (CISPROQUIM by its Spanish abbreviation in) is analyzed here using a demographic clustering technique. Data-quality processes were performed on the raw data (more than 170 variables) and as a result the database was reduced to 20 meaningful variables. The variables characterized by values with categories were selected for clustering analysis: gender, age, type of emergency, emergency location, means of poisoning, product use, and physical state of the toxic substance. Clustering analysis showed that there are three profiles that are prevalent in the TED database: Young Adult Suicidal Woman, Unsupervised Child, and Man at Work. These profiles could not be identified using traditional statistical analyses performed on the data collected by CISPROQUIM or defined a priori from the categorical variables. The identification of vulnerable populations and the cause of the toxicological events are critical in order to develop national prevention programs and policies. The analysis described provided a methodology for a critical analysis of toxicological databases that can be applied to other databases such as security databases.     

Databases and software for the analysis of mutations in the human p53 gene, the human hprt gene and both the lacI and lacZ gene in transgenic rodents.

We have created databases and software applications for the analysis of DNA mutations at the humanp53gene, the humanhprtgene and both the rodent transgeniclacIandlacZlocus. The databases themselves are stand-alone dBASE files and the software for analysis of the databases runs on IBM-compatible computers. Each database has a separate software analysis program. The software created for these databases permit the filtering, ordering, report generation and display of information in the database. In addition, a significant number of routines have been developed for the analysis of single base substitutions. One method of obtaining the databases and software is via the World Wide Web (WWW). Open the following home page with a Web Browser: http://sunsite.unc.edu/dnam/mainpage.ht ml . Alternatively, the databases and programs are available via public FTP from: anonymous@sunsite.unc.edu . There is no password required to enter the system. The databases and software are found beneath the subdirectory: pub/academic/biology/dna-mutations. Two other programs are available at the site-a program for comparison of mutational spectra and a program for entry of mutational data into a relational database.     

UniProt archive

UniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references; all other information must be retrieved from the source databases.     

Databases and software for the analysis of mutations in the human p53 gene, human hprt gene and both the lacI and lacZ gene in transgenic rodents.

We have created databases and software applications for the analysis of DNA mutations at the human p53 gene, the human hprt gene and both the rodent transgenic lacI and lacZ loci. The databases themselves are stand-alone dBASE files and the software for analysis of the databases runs on IBM-compatible computers with Microsoft Windows. Each database has a separate software analysis program. The software created for these databases permit the filtering, ordering, report generation and display of information in the database. In addition, a significant number of routines have been developed for the analysis of single base substitutions. One method of obtaining the databases and software is via the World Wide Web. Open the following home page with a Web Browser: http://sunsite.unc.edu/dnam/mainpage. html . Alternatively, the databases and programs are available via public FTP from: anonymous@sunsite.unc.edu. There is no password required to enter the system. The databases and software are found beneath the subdirectory: pub/academic/biology/dna-mutations. Two other programs are available at the site, a program for comparison of mutational spectra and a program for entry of mutational data into a relational database.     

FlyNets and GIF-DB, two internet databases for molecular interactions in Drosophila melanogaster.

GIF-DB and FlyNets are two WWW databases describing molecular (protein-DNA, protein-RNA and protein-protein) interactions occuring in the fly Drosophila melanogaster (http://gifts.univ-mrs.fr/GIFTS_home_page.html ). GIF-DB is a specialised database which focuses on molecular interactions involved in the process of embryonic pattern formation, whereas FlyNets is a new and more general database, the long-term goal of which is to report on any published molecular interaction occuring in the fly. The information content of both databases is distributed in specific lines arranged into an EMBL- (or GenBank-) like format. These databases achieve a high level of integration with other databases such as FlyBase, EMBL, GenBank and SWISS-PROT through numerous hyperlinks. In addition, we also describe SOS-DGDB, a new collection of annotated Drosophila gene sequences, in which binding sites for regulatory proteins are directly visible on the DNA primary sequence and hyperlinked both to GIF-DB and TRANSFAC database entries.     

The construction of a bioactive peptide database in Metazoa

Bioactive peptides play critical roles in regulating most biological processes in animals, and have considerable biological, medical and industrial importance. A number of peptides have been discovered usually based on their biological activities in vitro or based on their sequence similarities in silico. Through searches in Swiss-Prot and Trembl protein databases using BLAST alignment tools and other in silico methods, all currently known bioactive peptides and their precursor proteins are extracted. In addition, 132 recently discovered putative peptide genes in Drosophila as well as their orthologs in other species are collected. In total, 20 027 bioactive peptides from 19 438 precursor proteins covering 2820 metazoan species are retained, and they, respectively, make up a peptide and a peptide precursor database. The peptides and peptide precursor proteins are further classified into 373 families, 178 of which are represented by Prosite Pfam or Smart motifs, or by typical peptide motifs that have been constructed recently. The remaining 195 families are novel peptide families. The motifs characterizing the 178 peptide families are saved into a peptide motif database. The peptide, peptide precursor and peptide motif databases (version 1.0) are the most complete peptide, precursor and peptide motif collection in Metazoa so far. They are available on the WWW at http://www.peptides.be/.     

From information to understanding: the role of model organism databases in comparative and functional genomics

Data integration is key to functional and comparative genomics because integration allows diverse data types to be evaluated in new contexts. To achieve data integration in a scalable and sensible way, semantic standards are needed, both for naming things (standardized nomenclatures, use of key words) and also for knowledge representation. The Mouse Genome Informatics database and other model organism databases help to close the gap between information and understanding of biological processes because these resources enforce well-defined nomenclature and knowledge representation standards. Model organism databases have a critical role to play in ensuring that diverse kinds of data, especially genome-scale data sets and information, remain useful to the biological community in the long-term. The efforts of model organism database groups ensure not only that organism-specific data are integrated, curated and accessible but also that the information is structured in such a way that comparison of biological knowledge across model organisms is facilitated.