465 research outputs found
Analisis Struktur Gerak Tari Soongpak Suku Dayak Kayaan Medalaam Kabupaten Kapuas Hulu
The purpose of this research is to analysis of this Soongpak dance movement is done with separated the components of it and found the relationship each of the components until it made a wholeness of a dance. This research was conducted using descriptive analysis with qualitative and etnocoreology approachment. In this Soongpak dance the researcher found three clusters of movement, they are: two clusters as a introduction, and one more cluster as content and closing. the costume that is worn in this dance was the traditional costume of Kayaan. The music of this dance is Daak Soongpak that sounded with Sape\u27 or Sape\u27 Dua\u27 Ting. The floor pattern that has shaped was plain. It was only long line up and straight-walk with horizontal line. This Soongpak dance can be used as a lesson plan in teaching and learning activities and teaching theory and also the practical work in Culture and Skill Art (Seni Budaya dan Keterampilan) lesson
Analisis Musik Vokal Talimaa\u27 Suku Dayak Kayaan Medalaam Kapuas Hulu
This research based on the lack of interest for traditional art which is an ancestors heritage and the need for some effort to learn and preserve traditional music. One of traditional art that almost extinct and start to be unfamiliar by its own people is vocal music of Talimaa\u27 of Dayak Kayaan Medalaam tribe in Kapuas Hulu district. The purpose of this research is: 1) describing melody and shape of Talimaa\u27; 2) describing the vocal abilities required from a penalimaa\u27; 3) describing contextual aspect from Talimaa\u27. Method used in this research is quantitative descriptive method and use musicology approach. Data contained in this research is the result of direct observation and interview with informant about melody and shape of Talimaa\u27, vocal abilities required from a penalimaa\u27 and contextual aspect from Talimaa\u27. Data were analyzed qualitatively, with some interviewers, Maria Magdalena Ana Havi, Gregorius Jaang, Alel Sano, Ignatius Sebastian Paran, Aloysius Mering and some artist and some people who active and know about traditional vocal music, especially vocal music Talimaa\u27 of Dayak Kayaan Medalaam tribe
Distance, dissimilarity index, and network community structure
We address the question of finding the community structure of a complex
network. In an earlier effort [H. Zhou, {\em Phys. Rev. E} (2003)], the concept
of network random walking is introduced and a distance measure defined. Here we
calculate, based on this distance measure, the dissimilarity index between
nearest-neighboring vertices of a network and design an algorithm to partition
these vertices into communities that are hierarchically organized. Each
community is characterized by an upper and a lower dissimilarity threshold. The
algorithm is applied to several artificial and real-world networks, and
excellent results are obtained. In the case of artificially generated random
modular networks, this method outperforms the algorithm based on the concept of
edge betweenness centrality. For yeast's protein-protein interaction network,
we are able to identify many clusters that have well defined biological
functions.Comment: 10 pages, 7 figures, REVTeX4 forma
Duplication-divergence model of protein interaction network
We show that the protein-protein interaction networks can be surprisingly
well described by a very simple evolution model of duplication and divergence.
The model exhibits a remarkably rich behavior depending on a single parameter,
the probability to retain a duplicated link during divergence. When this
parameter is large, the network growth is not self-averaging and an average
vertex degree increases algebraically. The lack of self-averaging results in a
great diversity of networks grown out of the same initial condition. For small
values of the link retention probability, the growth is self-averaging, the
average degree increases very slowly or tends to a constant, and a degree
distribution has a power-law tail.Comment: 8 pages, 13 figure
eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses
eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de
eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges
Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721â801 orthologous groups, encompassing a total of 4â396â591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101â208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450â904 orthologous groups (62.5%)
PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment
<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) are crucial for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. Given the importance of PPIs, several methods have been developed to detect them. Since the experimental methods are time-consuming and expensive, developing computational methods for effectively identifying PPIs is of great practical significance.</p> <p>Findings</p> <p>Most previous methods were developed for predicting PPIs in only one species, and do not account for probability estimations. In this work, a relatively comprehensive prediction system was developed, based on a support vector machine (SVM), for predicting PPIs in five organisms, specifically humans, yeast, <it>Drosophila</it>, <it>Escherichia coli</it>, and <it>Caenorhabditis elegans</it>. This PPI predictor includes the probability of its prediction in the output, so it can be used to assess the confidence of each SVM prediction by the probability assignment. Using a probability of 0.5 as the threshold for assigning class labels, the method had an average accuracy for detecting protein interactions of 90.67% for humans, 88.99% for yeast, 90.09% for <it>Drosophila</it>, 92.73% for <it>E. coli</it>, and 97.51% for <it>C. elegans</it>. Moreover, among the correctly predicted pairs, more than 80% were predicted with a high probability of â„0.8, indicating that this tool could predict novel PPIs with high confidence.</p> <p>Conclusions</p> <p>Based on this work, a web-based system, Pred_PPI, was constructed for predicting PPIs from the five organisms. Users can predict novel PPIs and obtain a probability value about the prediction using this tool. Pred_PPI is freely available at <url>http://cic.scu.edu.cn/bioinformatics/predict_ppi/default.html</url>.</p
Identification and Functional Characterization of Gene Components of Type VI Secretion System in Bacterial Genomes
A new secretion system, called the Type VI Secretion system (T6SS), was recently reported in Vibrio cholerae, Pseudomonas aeruginosa and Burkholderia mallei. A total of 18 genes have been identified to be belonging to this secretion system in V. cholerae. Here we attempt to identify presence of T6SS in other bacterial genomes. This includes identification of orthologous sequences, conserved motifs, domains, families, 3D folds, genomic islands containing T6SS components, phylogenetic profiles and protein-protein association of these components. Our analysis indicates presence of T6SS in 42 bacteria and its absence in most of their non-pathogenic species, suggesting the role of T6SS in imparting pathogenicity to an organism. Analysis of genomic regions containing T6SS components, phylogenetic profiles and protein-protein association of T6SS components indicate few additional genes which could be involved in this secretion system. Based on our studies, functional annotations were assigned to most of the components. Except one of the genes, we could group all the other genes of T6SS into those belonging to the puncturing device, and those located in the outer membrane, transmembrane and inner membrane. Based on our analysis, we have proposed a model of T6SS and have compared the same with the other bacterial secretion systems
Revisiting Date and Party Hubs: Novel Approaches to Role Assignment in Protein Interaction Networks
The idea of 'date' and 'party' hubs has been influential in the study of
protein-protein interaction networks. Date hubs display low co-expression with
their partners, whilst party hubs have high co-expression. It was proposed that
party hubs are local coordinators whereas date hubs are global connectors. Here
we show that the reported importance of date hubs to network connectivity can
in fact be attributed to a tiny subset of them. Crucially, these few, extremely
central, hubs do not display particularly low expression correlation,
undermining the idea of a link between this quantity and hub function. The
date/party distinction was originally motivated by an approximately bimodal
distribution of hub co-expression; we show that this feature is not always
robust to methodological changes. Additionally, topological properties of hubs
do not in general correlate with co-expression. Thus, we suggest that a
date/party dichotomy is not meaningful and it might be more useful to conceive
of roles for protein-protein interactions rather than individual proteins. We
find significant correlations between interaction centrality and the functional
similarity of the interacting proteins.Comment: 27 pages, 5 main figures, 4 supplementary figure
Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years
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