18861193
An agent-based system to discover protein-protein interactions, identify protein complexes and proteins with multiple peptide mass fingerprints
Proteins "work together" by actually binding to form multicomponent complexes that carry out specific functions. Proteomic analyses based on the mass spectrum are now key methods to determine the components in protein complexes. The protein-protein interaction or functional association may be known to exist among the extracted protein spots while analyzing the proteins on the 2D gel. In this study, we develop an agent-based system, namely AgentMultiProtIdent, which integrated two protein identification tools and a variety of databases storing relations among proteins and used to discover protein-protein interactions and protein functional associations, and identify protein complexes and proteins with multiple peptide mass fingerprints as input. The system takes Multiple Peptide Mass Fingerprints (PMFs) as a whole in the protein complex or protein identification. With the relations among proteins, it may greatly improve the accuracy of identification of protein complexes. Also, possible relationship of the multiple peptide mass fingerprints, such as ontology relation, can be discovered by our system, especially in the identification of protein complexes. The agent-based system is now available on the Web at http://dbms104.csie.ncu.edu.tw/ approximately protein/NEW2/.
1841883
Mining putative regulatory elements in gene promoter regions of Saccharomyces cerevisiae
The availability of genome-wide gene expression data provides a unique set of genes from which we can decipher the mechanisms underlying the common transcriptional response. Transcription factors, which can bind to specific DNA sites, cooperatively regulate the transcription of genes. This study attempts to mine putative binding sites to investigate how combinations of the sites predicted from known sites and over-represented repetitive elements are distributed in the promoter regions of groups of functionally related genes. The over-represented repetitive elements appearing in the associations are possible transcription factor binding sites. The deduced association rules would facilitate to predict putative regulatory elements and to identify genes which are potentially co-regulated by the putative regulatory elements. Our proposed approach is applied to Saccharomyces cerevisiae and the promoter regions of yeast ORFs.
12419359
Primer design for multiplex PCR using a genetic algorithm
Multiplex Polymerase Chain Reaction (PCR) experiments are used for amplifying several segments of the target DNA simultaneously and thereby to conserve template DNA, reduce the experimental time, and minimize the experimental expense. The success of the experiment is dependent on primer design. However, this can be a dreary task as there are many constrains such as melting temperatures, primer length, GC content and complementarity that need to be optimized to obtain a good PCR product. Motivated by the lack of primer design tools for multiplex PCR genotypic assay, we propose a multiplex PCR primer design tool using a genetic algorithm, which is a stochastic approach based on the concept of biological evolution, biological genetics and genetic operations on chromosomes, to find an optimal selection of primer pairs for multiplex PCR experiments. The presented experimental results indicate that the proposed algorithm is capable of finding a series of primer pairs that obeies the design properties in the same tube.
13750244
A database to aid probe design for virus identification
FENG-MAO LIN, HSIEN-DA HUANG, YU-CHUNG CHANG, PAK-LEONG CHAN, JORNG-TZONG HORNG, MING-TAT KO Department of Computer Science and Information Engineering, National Central University, No.300, Jungda Rd, Jhongli City, Taoyuan, Taiwan 320 ChungLi, 320, Taiwan Department of Biological Science and Technology & Institute of Bioinformatic, National ChiaoTung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300 Hsin-Chu, 300, Taiwan Department of Biotechnology, Ming Chuan University, 250 Chung Shan North Road, Section 5, Taipei, 111, Taiwan Institute of Information Science, Academia Sinica, 128 Sec. 2, Academia Rd, Nankangm, Taipei, 115, Taiwan
5048088
KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites
KinasePhos is a novel web server for computationally identifying catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the profile hidden Markov model, computational models are learned from the kinase-specific groups of the phosphorylation sites. After evaluating the learned models, the model with highest accuracy was selected from each kinase-specific group, for use in a web-based prediction tool for identifying protein phosphorylation sites. Therefore, this work developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. The prediction tool is freely available at .
3255925
A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome
Very large-scale gene expression analysis, i.e., UniGene and dbEST, are provided to find those genes with significantly differential expression in specific tissues. The differentially expressed genes in a specific tissue are potentially regulated concurrently by a combination of transcription factors. This study attempts to mine putative binding sites on how combinations of the known regulatory sites homologs and over-represented repetitive elements are distributed in the promoter regions of considered groups of differentially expressed genes. We propose a data mining approach to statistically discover the significantly tissue-specific combinations of known site homologs and over-represented repetitive sequences, which are distributed in the promoter regions of differential gene groups. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements.
6603995
Protein family classification and functional annotation
With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.
15818599
Efficient Registration of 3D SPHARM Surfaces
We present SHREC, an efficient algorithm for registration of 3D SPHARM (spherical harmonic) surfaces. SHREC follows the iterative closest point (ICP) registration strategy, and alternately improves the surface correspondence and adjusts the object pose. It establishes the surface correspondence by aligning the underlying SPHARM parameterization. It employs a rotational property of the harmonic expansion to accelerate its step for parameterization rotation. It uses a hierarchical icosahedron approach to sample the rotation space and searches for the best parameterization that matches the template. Our experimental results show that SHREC can not only create more accurate registration than previous methods but also do it efficiently. SHREC is a simple, efficient and general registration method, and has a great potential to be used in many shape modeling and analysis applications.
11189498
On the spanning connectivity of graphs
Abstract A k-container C ( u , v ) of G between u and v is a set of k internally disjoint paths between u and v . A k -container C ( u , v ) of G is a k * - container if it contains all vertices of G . A graph G is k * - connected if there exists a k * -container between any two distinct vertices. The spanning connectivity of G , κ * ( G ) , is defined to be the largest integer k such that G is w * -connected for all 1 ⩽ w ⩽ k if G is a 1 * -connected graph. In this paper, we prove that κ * ( G ) ⩾ 2 δ ( G ) - n ( G ) + 2 if ( n ( G ) / 2 ) + 1 ⩽ δ ( G ) ⩽ n ( G ) - 2 . Furthermore, we prove that κ * ( G - T ) ⩾ 2 δ ( G ) - n ( G ) + 2 - | T | if T is a vertex subset with | T | ⩽ 2 δ ( G ) - n ( G ) - 1 .
19037242
iProClass: an integrated database of protein family, function and structure information
The iProClass database provides comprehensive, value-added descriptions of proteins and serves as a framework for data integration in a distributed networking environment. The protein information in iProClass includes family relationships as well as structural and functional classifications and features. The current version consists of about 830 000 non-redundant PIR-PSD, SWISS-PROT, and TrEMBL proteins organized with more than 36 000 PIR superfamilies, 145 000 families, 4000 domains, 1300 motifs and 550 000 FASTA similarity clusters. It provides rich links to over 50 database of protein sequences, families, functions and pathways, protein-protein interactions, post-translational modifications, protein expressions, structures and structural classifications, genes and genomes, ontologies, literature and taxonomy. Protein and superfamily summary reports present extensive annotation information and include membership statistics and graphical display of domains and motifs. iProClass employs an open and modular architecture for interoperability and scalability. It is implemented in the Oracle object-relational database system and is updated biweekly. The database is freely accessible from the web site at http://pir.georgetown.edu/iproclass/ and searchable by sequence or text string. The data integration in iProClass supports exploration of protein relationships. Such knowledge is fundamental to the understanding of protein evolution, structure and function and crucial to functional genomic and proteomic research.
38419730
Combined Encryption and Watermarking Approaches for Scalable Multimedia Coding
Intellectual Property (IP) protection is a critical element in a multimedia transmission system. Conventional IP protection schemes can be categorized into two major branches: encryption and watermarking. In this paper, a structure to perform layered access protection by combining encryption and robust watermarking is proposed and implemented. By taking advantage of the nature of cryptographic schemes and digital watermarking, the copyright of multimedia contents can be well protected. We adopt the scalable transmission method over the broadcasting environment. The embedded watermark can be thus extracted with high confidence. Then, the next-layer secrets can be perfectly decrypted and reconstructed. Finally, the media contents are recovered.