CaGE: cardiac gene expression knowledgebase

CaGE is a Cardiac Gene Expression knowledgebase we have developed to facilitate the analysis of genes important to human cardiac function. CaGE integrates the functionality of the LocusLink database with data from several human cardiac expression libraries, phenotypic data from OMIM and data from large-scale microarray gene expression studies to create a knowledgebase of gene expression in human cardiac tissue. The knowledgebase is fully searchable via the web using several intuitive query interfaces. Results can be displayed in several concise easy to navigate formats. AVAILABILITY: CaGE is located at http://www.cage.wbmei.jhu.edu     

DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

Background  

Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis.     

Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences

Background  

The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity.     

MaXML: mouse annotation XML

Although the sequencing of the human genome and several model organisms is almost complete, the number of genes in the human is still in debate. cDNA (complementary DNA) is generated from mRNA that is transcribed from the genome and can be regarded as a gene itself; therefore, decoding cDNA sequences is important in characterizing genes. Recently, biologists have been able to describe more knowledge about genes in order to characterize them, and this information is generally called 'annotation.' Furthermore, annotation is important in understanding the systems of organisms in various fields of research. We therefore constructed the MaXML (Mouse annotation XML) format with which mouse cDNA annotation data can be exchanged and shared between laboratories more efficiently. Defining strict data types for annotations is difficult, but we consider XML a feasible format for describing them. We have used the MaXML format to express mouse annotation data in FANTOM DB. We have also developed tools and systems utilizing these MaXML data, including a parser and a server to provide data on-the-fly.     

Using online tools at the Bovine Genome Database to manually annotate genes in the new reference genome

With the availability of a new highly contiguous Bos taurus reference genome assembly (ARS-UCD1.2), it is the opportune time to upgrade the bovine gene set by seeking input from researchers. Furthermore, advances in graphical genome annotation tools now make it possible for researchers to leverage sequence data generated with the latest technologies to collaboratively curate genes. For many years the Bovine Genome Database (BGD) has provided tools such as the Apollo genome annotation editor to support manual bovine gene curation. The goal of this paper is to explain the reasoning behind the decisions made in the manual gene curation process while providing examples using the existing BGD tools. We will describe the sources of gene annotation evidence provided at the BGD, including RNA-seq and Iso-Seq data. We will also explain how to interpret various data visualizations when curating gene models, and will demonstrate the value of manual gene annotation. The process described here can be applied to manual gene curation for other species with similar tools. With a better understanding of manual gene annotation, researchers will be encouraged to edit gene models and contribute to the enhancement of livestock gene sets.     

面向大规模人群的基因组注释系统

基因组注释是识别出基因组序列中功能组件的过程,其可以直接对序列赋予生物学意义,由此方便研究者探究和分析基因组功能.基因组注释可以帮助研究从三个层次上理解基因组,一种是在核苷酸水平的注释,主要确定DNA序列中基因、RNA、重复序列等组件的物理位置,包括转录起始,翻译起始,外显子边界等具体位置信息.同时可以注释得到变异在不...     

ProRule: a new database containing functional and structural information on PROSITE profiles

MOTIVATION: Increase the discriminatory power of PROSITE profiles to facilitate function determination and provide biologically relevant information about domains detected by profiles for the annotation of proteins. SUMMARY: We have created a new database, ProRule, which contains additional information about PROSITE profiles. ProRule contains notably the position of structurally and/or functionally critical amino acids, as well as the condition they must fulfill to play their biological role. These supplementary data should help function determination and annotation of the UniProt Swiss-Prot knowledgebase. ProRule also contains information about the domain detected by the profile in the Swiss-Prot line format. Hence, ProRule can be used to make Swiss-Prot annotation more homogeneous and consistent. The format of ProRule can be extended to provide information about combination of domains. AVAILABILITY: ProRule can be accessed through ScanProsite at http://www.expasy.org/tools/scanprosite. A file containing the rules will be made available under the PROSITE copyright conditions on our ftp site (ftp://www.expasy.org/databases/prosite/) by the next PROSITE release.     

The JCVI standard operating procedure for annotating prokaryotic metagenomic shotgun sequencing data

The JCVI metagenomics analysis pipeline provides for the efficient and consistent annotation of shotgun metagenomics sequencing data for sampling communities of prokaryotic organisms. The process can be equally applied to individual sequence reads from traditional Sanger capillary electrophoresis sequences, newer technologies such as 454 pyrosequencing, or sequence assemblies derived from one or more of these data types. It includes the analysis of both coding and non-coding genes, whether full-length or, as is often the case for shotgun metagenomics, fragmentary. The system is designed to provide the best-supported conservative functional annotation based on a combination of trusted homology-based scientific evidence and computational assertions and an annotation value hierarchy established through extensive manual curation. The functional annotation attributes assigned by this system include gene name, gene symbol, GO terms, EC numbers, and JCVI functional role categories.     

The institute for genomic research Osa1 rice genome annotation database

We have developed a rice (Oryza sativa) genome annotation database (Osa1) that provides structural and functional annotation for this emerging model species. Using the sequence of O. sativa subsp. japonica cv Nipponbare from the International Rice Genome Sequencing Project, pseudomolecules, or virtual contigs, of the 12 rice chromosomes were constructed. Our most recent release, version 3, represents our third build of the pseudomolecules and is composed of 98% finished sequence. Genes were identified using a series of computational methods developed for Arabidopsis (Arabidopsis thaliana) that were modified for use with the rice genome. In release 3 of our annotation, we identified 57,915 genes, of which 14,196 are related to transposable elements. Of these 43,719 non-transposable element-related genes, 18,545 (42.4%) were annotated with a putative function, 5,777 (13.2%) were annotated as encoding an expressed protein with no known function, and the remaining 19,397 (44.4%) were annotated as encoding a hypothetical protein. Multiple splice forms (5,873) were detected for 2,538 genes, resulting in a total of 61,250 gene models in the rice genome. We incorporated experimental evidence into 18,252 gene models to improve the quality of the structural annotation. A series of functional data types has been annotated for the rice genome that includes alignment with genetic markers, assignment of gene ontologies, identification of flanking sequence tags, alignment with homologs from related species, and syntenic mapping with other cereal species. All structural and functional annotation data are available through interactive search and display windows as well as through download of flat files. To integrate the data with other genome projects, the annotation data are available through a Distributed Annotation System and a Genome Browser. All data can be obtained through the project Web pages at http://rice.tigr.org.     

Protein function prediction and annotation in an integrated environment powered by web services (AFAWE)

Many sequenced genes are mainly annotated through automatic transfer of annotation from similar sequences. Manual comparison of results or intermediate results from different tools can help avoid wrong annotations and give hints to the function of a gene even if none of the automated tools could return any result. AFAWE simplifies the task of manual functional annotation by running different tools and workflows for automatic function prediction and displaying the results in a way that facilitates comparison. Because all programs are executed as web services, AFAWE is easily extensible and can directly query primary databases, thereby always using the most up-to-date data sources. Visual filters help to distinguish trustworthy results from non-significant results. Furthermore, an interface to add detailed manual annotation to each gene is provided, which can be displayed to other users.