Creation of FRIENDSPERK Platform for Social Network

Social Networking. It's the way the 21st century imparts now. Person to person communication is the gathering of people into particular gatherings, similar to little rustic groups or an area subdivision. Albeit long range interpersonal communication is conceivable in individual, particularly in the work environment, colleges, and secondary schools, it is most well-known on the web. This is on the grounds that not at all like most secondary schools, universities, or work environments, the web is loaded with a great many people why should looking meet other individuals

KNOTTIN: the knottin or inhibitor cystine knot scaffold in 2007

The KNOTTIN database provides standardized information on the small disulfide-rich proteins with a knotted topology called knottins or inhibitor cystine knots. Static pages present the essential historical or recent results about knottin discoveries, sequences, structures, syntheses, folding, functions, applications and bibliography. New tools, KNOTER3D and KNOTER1D, are provided to determine or predict if a user query (3D structure or sequence) is a knottin. These tools are now used to automate the database update. All knottin structures and sequences in the database are now standardized according to the knottin nomenclature based on loop lengths between knotted cysteines, and to the knottin numbering scheme. Therefore, the whole KNOTTIN database (sequences and structures) can now be searched using loop lengths, in addition to keyword and sequence (BLAST, HMMER) searches. Renumbered and structurally fitted knottin PDB files are available for download as well as renumbered sequences, sequence alignments and logos. The knottin numbering scheme is used for automatic drawing of standardized two-dimensional Colliers de Perles of any knottin structure or sequence in the database or provided by the user. The KNOTTIN database is available at http://knottin.cbs.cnrs.fr

The human homologue of unc-93 maps to chromosome 6q27 – characterisation and analysis in sporadic epithelial ovarian cancer

BACKGROUND: In sporadic ovarian cancer, we have previously reported allele loss at D6S193 (62%) on chromosome 6q27, which suggested the presence of a putative tumour suppressor gene. Based on our data and that from another group, the minimal region of allele loss was between D6S264 and D6S149 (7.4 cM). To identify the putative tumour suppressor gene, we established a physical map initially with YACs and subsequently with PACs/BACs from D6S264 to D6S149. To accelerate the identification of genes, we sequenced the entire contig of approximately 1.1 Mb. Seven genes were identified within the region of allele loss between D6S264 and D6S149. RESULTS: The human homologue of unc-93 (UNC93A) in C. elegans was identified to be within the interval of allele loss centromeric to D6S149. This gene is 24.5 kb and comprises of 8 exons. There are two transcripts with the shorter one due to splicing out of exon 4. It is expressed in testis, small intestine, spleen, prostate, and ovary. In a panel of 8 ovarian cancer cell lines, UNC93A expression was detected by RT-PCR which identified the two transcripts in 2/8 cell lines. The entire coding sequence was examined for mutations in a panel of ovarian tumours and ovarian cancer cell lines. Mutations were identified in exons 1, 3, 4, 5, 6 and 8. Only 3 mutations were identified specifically in the tumour. These included a c.452G>A (W151X) mutation in exon 3, c.676C>T (R226X) in exon 5 and c.1225G>A(V409I) mutation in exon 8. However, the mutations in exon 3 and 5 were also present in 6% and 2% of the normal population respectively. The UNC93A cDNA was shown to express at the cell membrane and encodes for a protein of 60 kDa. CONCLUSIONS: These results suggest that no evidence for UNC93A as a tumour suppressor gene in sporadic ovarian cancer has been identified and further research is required to evaluate its normal function and role in the pathogenesis of ovarian cancer

EVEREST: automatic identification and classification of protein domains in all protein sequences

BACKGROUND: Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Whereas sequencing technologies have advanced immensely in recent years, there are no matching computational methodologies for large-scale determination of protein domains and their boundaries. We provide and rigorously evaluate a novel set of domain families that is automatically generated from sequence data. Our domain family identification process, called EVEREST (EVolutionary Ensembles of REcurrent SegmenTs), begins by constructing a library of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families. The selection of the best putative families is done using machine learning techniques. A statistical model is then created for each of the chosen families. This procedure is then iterated: the aforementioned statistical models are used to scan all protein sequences, to recreate a library of segments and to cluster them again. RESULTS: Processing the Swiss-Prot section of the UniProt Knoledgebase, release 7.2, EVEREST defines 20,230 domains, covering 85% of the amino acids of the Swiss-Prot database. EVEREST annotates 11,852 proteins (6% of the database) that are not annotated by Pfam A. In addition, in 43,086 proteins (20% of the database), EVEREST annotates a part of the protein that is not annotated by Pfam A. Performance tests show that EVEREST recovers 56% of Pfam A families and 63% of SCOP families with high accuracy, and suggests previously unknown domain families with at least 51% fidelity. EVEREST domains are often a combination of domains as defined by Pfam or SCOP and are frequently sub-domains of such domains. CONCLUSION: The EVEREST process and its output domain families provide an exhaustive and validated view of the protein domain world that is automatically generated from sequence data. The EVEREST library of domain families, accessible for browsing and download at [1], provides a complementary view to that provided by other existing libraries. Furthermore, since it is automatic, the EVEREST process is scalable and we will run it in the future on larger databases as well. The EVEREST source files are available for download from the EVEREST web site

Optimizing structural modeling for a specific protein scaffold: knottins or inhibitor cystine knots

<p>Abstract</p> <p>Background</p> <p>Knottins are small, diverse and stable proteins with important drug design potential. They can be classified in 30 families which cover a wide range of sequences (1621 sequenced), three-dimensional structures (155 solved) and functions (> 10). Inter knottin similarity lies mainly between 15% and 40% sequence identity and 1.5 to 4.5 Å backbone deviations although they all share a tightly knotted disulfide core. This important variability is likely to arise from the highly diverse loops which connect the successive knotted cysteines. The prediction of structural models for all knottin sequences would open new directions for the analysis of interaction sites and to provide a better understanding of the structural and functional organization of proteins sharing this scaffold.</p> <p>Results</p> <p>We have designed an automated modeling procedure for predicting the three-dimensionnal structure of knottins. The different steps of the homology modeling pipeline were carefully optimized relatively to a test set of knottins with known structures: template selection and alignment, extraction of structural constraints and model building, model evaluation and refinement. After optimization, the accuracy of predicted models was shown to lie between 1.50 and 1.96 Å from native structures at 50% and 10% maximum sequence identity levels, respectively. These average model deviations represent an improvement varying between 0.74 and 1.17 Å over a basic homology modeling derived from a unique template. A database of 1621 structural models for all known knottin sequences was generated and is freely accessible from our web server at <url>http://knottin.cbs.cnrs.fr</url>. Models can also be interactively constructed from any knottin sequence using the structure prediction module Knoter1D3D available from our protein analysis toolkit PAT at <url>http://pat.cbs.cnrs.fr</url>.</p> <p>Conclusions</p> <p>This work explores different directions for a systematic homology modeling of a diverse family of protein sequences. In particular, we have shown that the accuracy of the models constructed at a low level of sequence identity can be improved by 1) a careful optimization of the modeling procedure, 2) the combination of multiple structural templates and 3) the use of conserved structural features as modeling restraints.</p

MOWServ: a web client for integration of bioinformatic resources

The productivity of any scientist is affected by cumbersome, tedious and time-consuming tasks that try to make the heterogeneous web services compatible so that they can be useful in their research. MOWServ, the bioinformatic platform offered by the Spanish National Institute of Bioinformatics, was released to provide integrated access to databases and analytical tools. Since its release, the number of available services has grown dramatically, and it has become one of the main contributors of registered services in the EMBRACE Biocatalogue. The ontology that enables most of the web-service compatibility has been curated, improved and extended. The service discovery has been greatly enhanced by Magallanes software and biodataSF. User data are securely stored on the main server by an authentication protocol that enables the monitoring of current or already-finished user’s tasks, as well as the pipelining of successive data processing services. The BioMoby standard has been greatly extended with the new features included in the MOWServ, such as management of additional information (metadata such as extended descriptions, keywords and datafile examples), a qualified registry, error handling, asynchronous services and service replication. All of them have increased the MOWServ service quality, usability and robustness. MOWServ is available at http://www.inab.org/MOWServ/ and has a mirror at http://www.bitlab-es.com/MOWServ/

Amchitka Island Environmental Analysis at Idaho National Laboratory

The Idaho National Laboratory (INL) provided support to Consortium for Risk Evaluation with Stakeholder Participation (CRESP) in their activities which is supported by the Department of Energy (DOE) to assess the impact of past nuclear testing at Amchitka Island on the ecosystemof the island and surrounding ocean. INL participated in this project in three phases, Phase 1, Phase 2 and Phase 3

Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees?

Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from −0.003 to −0.065 μmol CO2 m−2 s−1 day−1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees

A Computational Strategy for Protein Function Assignment Which Addresses the Multidomain Problem

A method for assigning functions to unknown sequences based on finding correlations between short signals and functional annotations in a protein database is presented. This approach is based on keyword (KW) and feature (FT) information stored in the SWISS-PROT database. The former refers to particular protein characteristics and the latter locates these characteristics at a specific sequence position. In this way, a certain keyword is only assigned to a sequence if sequence similarity is found in the position described by the FT field. Exhaustive tests performed over sequences with homologues (cluster set) and without homologues (singleton set) in the database show that assigning functions is much ’cleaner’ when information about domains (FT field) is used, than when only the keywords are used