Netscan: a procedure for generating reaction networks by size

In this paper, we describe an algorithm which can be used to generate the collection of networks, in order of increasing size, that are compatible with a list of chemical reactions and that satisfy a constraint. Our algorithm has been encoded and the software, called Netscan, can be freely downloaded from ftp://ftp.stat.ubc.ca/pub/riffraff/Netscanfiles, along with a manual, for general scientific use. Our algorithm may require pre-processing to ensure that the quantities it acts on are physically relevant and because it outputs sets of reactions, which we call canonical networks, that must be elaborated into full networks.     

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/     

In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks

Summary: We present In silico Biochemical Reaction Network Analysis(IBRENA), a software package which facilitates multiple functionsincluding cellular reaction network simulation and sensitivityanalysis (both forward and adjoint methods), coupled with principalcomponent analysis, singular-value decomposition and model reduction.The software features a graphical user interface that aids simulationand plotting of in silico results. While the primary focus isto aid formulation, testing and reduction of theoretical biochemicalreaction networks, the program can also be used for analysisof high-throughput genomic and proteomic data. Availability: The software package, manual and examples areavailable at http://www.eng.buffalo.edu/~neel/ibrena Contact: neel{at}eng.buffalo.edu Associate Editor: Limsoon Wong     

lca_algebraic: a library bringing symbolic calculus to LCA for comprehensive sensitivity analysis

The International Journal of Life Cycle Assessment - In this paper, we present new tools to ease the analysis of the effect of variability and uncertainty on life cycle assessment (LCA) results....     

PedVizApi: a Java API for the interactive, visual analysis of extended pedigrees

PedVizApi is a Java API (application program interface) for the visual analysis of large and complex pedigrees. It provides all the necessary functionality for the interactive exploration of extended genealogies. While available packages are mostly focused on a static representation or cannot be added to an existing application, PedVizApi is a highly flexible open source library for the efficient construction of visual-based applications for the analysis of family data. An extensive demo application and a R interface is provided. AVAILABILITY: http://www.pedvizapi.org     

BFL: a node and edge betweenness based fast layout algorithm for large scale networks

Background  

Network visualization would serve as a useful first step for analysis. However, current graph layout algorithms for biological pathways are insensitive to biologically important information, e.g. subcellular localization, biological node and graph attributes, or/and not available for large scale networks, e.g. more than 10000 elements.     

The backpropagation algorithm in J, a fast prototyping tool for researching neural networks

This paper illustrates the use of a powerful language, called J, that is ideal for simulating neural networks. The use of J is demonstrated by its application to a gradient descent method for training a multilayer perceptron. It is also shown how the back-propagation algorithm can be easily generalized to multilayer networks without any increase in complexity and that the algorithm can be completely expressed in an array notation which is directly executable through J. J is a general purpose language, which means that its user is given a flexibility not available in neural network simulators or in software packages such as MATLAB. Yet, because of its numerous operators, J allows a very succinct code to be used, leading to a tremendous decrease in development time.     

The use of high-resolution melting analysis for genotyping Symbiodinium strains: a sensitive and fast approach

High-resolution melting (HRM) analysis is a closed-tube, rapid and sensitive technique able to detect DNA variations. It relies on the fluorescence melting curves that are obtained from the transition of double-stranded DNA (dsDNA) to single-stranded DNA (ssDNA) as a result of temperature increase. In this study, we evaluated the effectiveness of HRM as a tool to rapidly and precisely genotype monotypic Symbiodinium populations using the internal transcribed spacer, region 2, ribosomal DNA (ITS2 rDNA). For this, Symbiodinium denaturing gradient gel electrophoresis (DGGE) profiles, where gel bands were excised and sequenced, were compared to HRM genotypes. Results showed that twenty cultures were correctly genotyped in <2 h using HRM analysis with a percentage of confidence >90%. Limitations of the technique were also investigated. Unlike other techniques used for genotyping Symbiodinium, such as DGGE and other fingerprint profiles, HRM is a technique of great advantage for field coral reef ecologists and physiologists as no expertise in advanced molecular methods is required.     

Expa: a program for calculating extreme pathways in biochemical reaction networks

SUMMARY: The set of extreme pathways, a generating set for all possible steady-state flux maps in a biochemical reaction network, can be computed from the stoichiometric matrix, an incidence-like matrix reflecting the network topology. Here, we describe the implementation of a well-known algorithm to compute these pathways and give a summary of the features of the available software. AVAILABILITY: The C-code, along with a Windows executable and sample network reaction files, are available at http://systemsbiology.ucsd.edu CONTACT: palsson@ucsd.edu.     

Identification of reaction networks for bioprocesses: determination of a partially unknown pseudo-stoichiometric matrix

In this paper we propose a methodology to determine the structure of the pseudo-stoichiometric coefficient matrix K in a mass balance-based model and to identify its coefficients from a set of available data. The first stage consists in estimating the number of reactions that must be taken into account to represent the main mass transfer within the bioreactor. This provides the dimension of K. Then we propose a method to directly determine the structure of the matrix (i.e. mainly its zeros and the signs of its coefficients). These methods are illustrated with simulations of a process of lipase production from olive oil by Candida rugosa.     

The role of disorder in interaction networks: a structural analysis

Recent studies have emphasized the value of including structural information into the topological analysis of protein networks. Here, we utilized structural information to investigate the role of intrinsic disorder in these networks. Hub proteins tend to be more disordered than other proteins (i.e. the proteome average); however, we find this only true for those with one or two binding interfaces (‘single’‐interface hubs). In contrast, the distribution of disordered residues in multi‐interface hubs is indistinguishable from the overall proteome. Surprisingly, we find that the binding interfaces in single‐interface hubs are highly structured, as is the case for multi‐interface hubs. However, the binding partners of single‐interface hubs tend to have a higher level of disorder than the proteome average, suggesting that their binding promiscuity is related to the disorder of their binding partners. In turn, the higher level of disorder of single‐interface hubs can be partly explained by their tendency to bind to each other in a cascade. A good illustration of this trend can be found in signaling pathways and, more specifically, in kinase cascades. Finally, our findings have implications for the current controversy related to party and date‐hubs.