A simple and fast secondary structure prediction method using hidden neural networks

MOTIVATION: In this paper, we present a secondary structure prediction method YASPIN that unlike the current state-of-the-art methods utilizes a single neural network for predicting the secondary structure elements in a 7-state local structure scheme and then optimizes the output using a hidden Markov model, which results in providing more information for the prediction. RESULTS: YASPIN was compared with the current top-performing secondary structure prediction methods, such as PHDpsi, PROFsec, SSPro2, JNET and PSIPRED. The overall prediction accuracy on the independent EVA5 sequence set is comparable with that of the top performers, according to the Q3, SOV and Matthew's correlations accuracy measures. YASPIN shows the highest accuracy in terms of Q3 and SOV scores for strand prediction. AVAILABILITY: YASPIN is available on-line at the Centre for Integrative Bioinformatics website (http://ibivu.cs.vu.nl/programs/yaspinwww/) at the Vrije University in Amsterdam and will soon be mirrored on the Mathematical Biology website (http://www.mathbio.nimr.mrc.ac.uk) at the NIMR in London. CONTACT: kxlin@nimr.mrc.ac.uk     

一种新的无标度网络构建方法及其在基因表达谱模拟上的应用

本文提出一种新的基于重连接方法的无标度网络构建算法．根据重连接方法新节点的调控节点会被重选,重连接概率取决于幂率分布模型参数gamma．用本文算法构建的网络通过微分方程模型来模拟基因表达谱数据,所用的优化算法为GA与PSO．候选节点的选择可以根据已有节点的连接数决定．实验的网络可以用log-log图,模拟的基因表达谱也用微分方程模型来验证效果．每个连接的正确性将会通过实验验证,完整的程序可以通过我们的官方网站获得：http://ccst.jlu.edu.cn/CSBG/ourown/.     

Predicting interactions in protein networks by completing defective cliques

Datasets obtained by large-scale, high-throughput methods for detecting protein-protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving the quality of these datasets by predicting missed protein-protein interactions, using only the topology of the protein interaction network observed by the large-scale experiment. The central idea of the method is to search the protein interaction network for defective cliques (nearly complete complexes of pairwise interacting proteins), and predict the interactions that complete them. We formulate an algorithm for applying this method to large-scale networks, and show that in practice it is efficient and has good predictive performance. More information can be found on our website http://topnet.gersteinlab.org/clique/ CONTACT: Mark.Gerstein@yale.edu SUPPLEMENTARY INFORMATION: Supplementary Materials are available at Bioinformatics online.     

Synapse signalling complexes and networks: machines underlying cognition

All thoughts and actions are encoded in patterns of neuronal electrical activity. Circuits of nerve cells connected by synapses are dedicated to processing information in these patterns. Information is not only transmitted across the synapse but also monitored by postsynaptic molecular machines. These machines are macromolecular complexes of approximately 100 proteins organised into a network of protein interactions. The network can be mathematically described as a scale-free network. Components of the complexes are necessary for decoding the neural code and converting electrical information into biochemical changes. The network properties of these complexes may explain many of the features of neuronal plasticity and cognitive function in rodents. Importantly, these multiprotein complexes and their network properties shed new light on the basis of human cognitive diseases including schizophrenia, autism, Huntington's disease and mental retardation. Supplementary material for this article can be found on the BioEssays website http://www.interscience.wiley.com/jpages/0265-9247/suppmat/index.html.     

Serial NetEvolve: a flexible utility for generating serially-sampled sequences along a tree or recombinant network

SUMMARY: Serial NetEvolve is a flexible simulation program that generates DNA sequences evolved along a tree or recombinant network. It offers a user-friendly Windows graphical interface and a Windows or Linux simulator with a diverse selection of parameters to control the evolutionary model. Serial NetEvolve is a modification of the Treevolve program with the following additional features: simulation of serially-sampled data, the choice of either a clock-like or a variable rate model of sequence evolution, sampling from the internal nodes and the output of the randomly generated tree or network in our newly proposed NeTwick format. AVAILABILITY: From website http://biorg.cis.fiu.edu/SNE Contacts: giri@cis.fiu.edu SUPPLEMENTARY INFORMATION: Manual and examples available from http://biorg.cis.fiu.edu/SNE.     

The lipocalin website

We introduce a website devoted to the lipocalins. The website contains data on lipocalin structures and sequences, as well as reviewing lipocalin biology and biochemistry. Our hope is that it can act as a focus for future research into the lipocalin protein family. The website can be accessed at the following URL: http://www. jenner.ac.uk/lipocalin.htm.     

The ESID Online Database network

Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform. AVAILABILITY: The ESID Online Database is accessible via the official website (http://www.esid.org/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Growing genetic regulatory networks from seed genes

MOTIVATION: A number of models have been proposed for genetic regulatory networks. In principle, a network may contain any number of genes, so long as data are available to make inferences about their relationships. Nevertheless, there are two important reasons why the size of a constructed network should be limited. Computationally and mathematically, it is more feasible to model and simulate a network with a small number of genes. In addition, it is more likely that a small set of genes maintains a specific core regulatory mechanism. RESULTS: Subnetworks are constructed in the context of a directed graph by beginning with a seed consisting of one or more genes believed to participate in a viable subnetwork. Functionalities and regulatory relationships among seed genes may be partially known or they may simply be of interest. Given the seed, we iteratively adjoin new genes in a manner that enhances subnetwork autonomy. The algorithm is applied using both the coefficient of determination and the Boolean-function influence among genes, and it is illustrated using a glioma gene-expression dataset. AVAILABILITY: Software for the seed-growing algorithm will be available at the website for Probabilistic Boolean Networks: http://www2.mdanderson.org/app/ilya/PBN/PBN.htm     

Development of a website and biobank database for the Nanosized Cancer Polymarker Biochip Project: a Multicenter Italian Experience

The Nanosized Cancer Polymarker Biochip Project (RBLA03S4SP) funded by an Italian MIUR-FIRB grant (Italian Ministry of University and Research - Investment Funds for Basic Research) has led to the creation of a free-access dynamic website, available at the web address https://serviziweb.ulss12.ve.it/firbabo, and of a centralized database with password-restricted access. The project network is composed of 9 research units (RUs) and has been active since 2005. The aim of the FIRB project was the design, production and validation of optoelectronic and chemoelectronic biosensors for the simultaneous detection of a novel class of cancer biomarkers associated with immunoglobulins of the M class (IgM) for early diagnosis of cancer. Biomarker immune complexes (BM-ICs) were assessed on samples of clinical cases and matched controls for breast, colorectal, liver, ovarian and prostate malignancies. This article describes in detail the architecture of the project website, the central database application, and the biobank developed for the FIRB Nanosized Cancer Polymarker Biochip Project. The article also illustrates many unique aspects that should be considered when developing a database within a multidisciplinary scenario. The main deliverables of the project were numerous, including the development of an online database which archived 1400 case report forms (700 cases and 700 matched controls) and more than 2700 experimental results relative to the BM-ICs assayed. The database also allowed for the traceability and retrieval of 21,000 aliquots archived in the centralized bank and stored as backup in the RUs, and for the development of a centralized biological bank in the coordinating unit with 6300 aliquots of serum. The constitution of the website and biobank database enabled optimal coordination of the RUs involved, highlighting the importance of sharing samples and scientific data in a multicenter setting for the achievement of the project goals.     

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. AVAILABILITY: http://cytoprophet.cse.nd.edu.     

The DynDom database of protein domain motions

A relational database has been developed based on the results from the application of the DynDom program to a number of proteins for which multiple X-ray conformers are available. The database is populated via a web-based tool that allows visitors to the website to run the DynDom program server-side by selecting pairs of X-ray conformers by Protein Data Bank code and chain identifier. AVAILABILITY: The website can be found at: http://www.sys.uea.ac.uk/dyndom.     

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks

Biological processes involve complex networks of interactions between molecules. Various large-scale experiments and curation efforts have led to preliminary versions of complete cellular networks for a number of organisms. To grapple with these networks, we developed TopNet-like Yale Network Analyzer (tYNA), a Web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs (such as feed-forward loops), calculating global statistics (such as the clustering coefficient and eccentricity), and identifying hubs and bottlenecks. It also allows one to manage a large number of private and public networks using a flexible tagging system, to filter them based on a variety of criteria, and to visualize them through an interactive graphical interface. A number of commonly used biological datasets have been pre-loaded into tYNA, standardized and grouped into different categories. AVAILABILITY: The tYNA system can be accessed at http://networks.gersteinlab.org/tyna. The source code, JavaDoc API and WSDL can also be downloaded from the website. tYNA can also be accessed from the Cytoscape software using a plugin.     

SEBINI: Software Environment for BIological Network Inference

The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and evaluation of algorithms used to reconstruct the structure of biological regulatory and interaction networks. SEBINI can be used to compare and train network inference methods on artificial networks and simulated gene expression perturbation data. It also allows the analysis within the same framework of experimental high-throughput expression data using the suite of (trained) inference methods; hence SEBINI should be useful to software developers wishing to evaluate, compare, refine or combine inference techniques, and to bioinformaticians analyzing experimental data. SEBINI provides a platform that aids in more accurate reconstruction of biological networks, with less effort, in less time. AVAILABILITY: A demonstration website is located at https://www.emsl.pnl.gov/NIT/NIT.html. The Java source code and PostgreSQL database schema are available freely for non-commercial use.     

Birth defects surveillance in Ukraine: a process

Birth defects (BD) surveillance using international standards was introduced in Ukraine by a network of five BD centers located in northwestern, central and southern regions. BD centers provide resources to access current and comprehensive information and to nurture partnerships with physicians, administrators, parental support groups, educators, and humanitarian assistance organizations. One outcome was the vigorous and popular website International BD Information Systems (IBIS). The network is now incorporated as OMNI-Net Ukraine. The program has documented high prevalence rates of neural tube defects (NTD); fetal alcohol effects (FAE); and idiopathic developmental retardation among orphans that prompted prevention and amelioration initiatives. Further program objectives include: universal folic acid flour fortification, as recommended by the Ukrainian Academy of Medicine; continued research on methods to reduce FAE in collaboration with partners from California; opening other early infant stimulation centers funded by local authorities, modeled on those in Rivne and Lutsk; and linking BD prevention with bioethical considerations, which is a topic of interest in Ukraine in part enhanced by the effects of Chornobyl.     

Development and implementation of standardized respiratory chain spectrophotometric assays for clinical diagnosis

Diversity of respiratory chain spectrophotometric assays may lead to difficult comparison of results between centers. The French network of mitochondrial diseases diagnostic centers undertook comparison of the results obtained with different protocols in the French diagnostic centers. The diversity of protocols was shown to have striking consequences, which prompted the network to undertake standardization and optimization of the protocols with respect to clinical diagnosis, i.e. high velocity while maintaining linear kinetics relative to time and enzyme concentration. Assays were set up on animal tissues and verified on control human muscle and fibroblasts.Influence of homogenization buffer and narrow range of optimal concentration of phosphate, substrate and tissue were shown. Experimental data and proposed protocols have been posted on a free access website. Their subsequent use in several diagnostic centers has improved consistency for all assays.     

ModuleRole: A Tool for Modulization,Role Determination and Visualization in Protein-Protein Interaction Networks

Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by “User Guide” in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user’s own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID.

Availability

ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be obtained upon request.     

Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle

MOTIVATION: To understand the behaviour of complex biological regulatory networks, a proper integration of molecular data into a full-fledge formal dynamical model is ultimately required. As most available data on regulatory interactions are qualitative, logical modelling offers an interesting framework to delineate the main dynamical properties of the underlying networks. RESULTS: Transposing a generic model of the core network controlling the mammalian cell cycle into the logical framework, we compare different strategies to explore its dynamical properties. In particular, we assess the respective advantages and limits of synchronous versus asynchronous updating assumptions to delineate the asymptotical behaviour of regulatory networks. Furthermore, we propose several intermediate strategies to optimize the computation of asymptotical properties depending on available knowledge. AVAILABILITY: The mammalian cell cycle model is available in a dedicated XML format (GINML) on our website, along with our logical simulation software GINsim (http://gin.univ-mrs.fr/GINsim). Higher resolution state transitions graphs are also found on this web site (Model Repository page).     

Design and Implementation of Website Information Disclosure Assessment System

Internet application technologies, such as cloud computing and cloud storage, have increasingly changed people’s lives. Websites contain vast amounts of personal privacy information. In order to protect this information, network security technologies, such as database protection and data encryption, attract many researchers. The most serious problems concerning web vulnerability are e-mail address and network database leakages. These leakages have many causes. For example, malicious users can steal database contents, taking advantage of mistakes made by programmers and administrators. In order to mitigate this type of abuse, a website information disclosure assessment system is proposed in this study. This system utilizes a series of technologies, such as web crawler algorithms, SQL injection attack detection, and web vulnerability mining, to assess a website’s information disclosure. Thirty websites, randomly sampled from the top 50 world colleges, were used to collect leakage information. This testing showed the importance of increasing the security and privacy of website information for academic websites.