Melanie R. Nelson

Bio: Melanie R. Nelson is an academic researcher from Scripps Research Institute. The author has contributed to research in topics: CellML & Calmodulin. The author has an hindex of 12, co-authored 15 publications receiving 3934 citations. Previous affiliations of Melanie R. Nelson include Science Applications International Corporation & Princeton University.

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

Abstract: 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. ∗ To whom correspondence should be addressed. Availability: The specification of SBML Level 1 is freely available from http://www.sbml.org/.

Structures of EF-hand Ca(2+)-binding proteins: diversity in the organization, packing and response to Ca2+ binding.

Abstract: The growing database of three-dimensional structures of EF-hand calcium-binding proteins is revealing a previously unrecognized variability in the coformations and organizations of EF-hand binding motifs. The structures of twelve different EF-hand proteins for which coordinates are publicly available are discussed and related to their respective biological and biophysical properties. The classical picture of calcium sensors and calcium signal modulators is presented, along with variants on the basic theme and new structural paradigms.© Kluwer Academic Publishers

An interaction‐based analysis of calcium‐induced conformational changes in Ca2+ sensor proteins

Abstract: Calcium sensor proteins translate transient increases in intracellular calcium levels into metabolic or mechanical responses, by undergoing dramatic conformational changes upon Ca2+ binding. A detailed analysis of the calcium binding-induced conformational changes in the representative calcium sensors calmodulin (CaM) and troponin C was performed to obtain insights into the underlying molecular basis for their response to the binding of calcium. Distance difference matrices, analysis of interresidue contacts, comparisons of interhelical angles, and inspection of structures using molecular graphics were used to make unbiased comparisons of the various structures. The calcium-induced conformational changes in these proteins are dominated by reorganization of the packing of the four helices within each domain. Comparison of the closed and open conformations confirms that calcium binding causes opening within each of the EF-hands. A secondary analysis of the conformation of the C-terminal domain of CaM (CaM-C) clearly shows that CaM-C occupies a closed conformation in the absence of calcium that is distinct from the semi-open conformation observed in the C-terminal EF-hand domains of myosin light chains. These studies provide insight into the structural basis for these changes and into the differential response to calcium binding of various members of the EF-hand calcium-binding protein family. Factors contributing to the stability of the Ca2+-loaded open conformation are discussed, including a new hypothesis that critical hydrophobic interactions stabilize the open conformation in Ca2+ sensors, but are absent in "non-sensor" proteins that remain closed upon Ca2+ binding. A role for methionine residues in stabilizing the open conformation is also proposed.

Incorporating Protein Environments in Density Functional Theory: A Self-Consistent Reaction Field Calculation of Redox Potentials of [2Fe2S] Clusters in Ferredoxin and Phthalate Dioxygenase Reductase

Abstract: An approach to calculating molecular electronic structures of active-site clusters in the presence of protein environments has been developed. The active-site cluster is treated by density functional theory. The protein field, together with the reaction field arising mainly from solvent, is obtained from a finite-difference solution to the Poisson−Boltzmann equation with three dielectric regions, and then these are coupled to the density functional calculation by a self-consistent iterative procedure. The method is applied to compute redox potentials of ferredoxin from Anabaena 7120 and phthalate dioxygenase reductase (PDR) from Pseudomonas cepacia, both having similar [Fe2S2(SR)4] active-site clusters. The calculated redox potentials, −1.007 V and −0.812 V in 0.05 M ionic strength for ferredoxin and PDR, respectively, deviate significantly from experimental values of −0.440 and −0.174 V. However, the calculated data reproduce the experimental trend fairly well. The calculated redox potential for PDR is 1...

A short introduction to CellML

Abstract: CellML TM is an XML–based language designed to facilitate the exchange of biological models across the World Wide Web. Processing applications are able to appropriately render models based on the definition of model structure given in a CellML document, and run simulations based on the definition of the underlying mathematics. CellML is designed to be a general framework upon which a wide variety of models may be built. The basic constituents and structure are simple, providing a common basis for describing models and facilitating the creation of complex models from simpler ones by combining models and/or adding detail to existing models. CellML models are represented as a collection of discrete components linked by connections to form a network. A component is a functional unit that may correspond to a physical compartment, a collection of entities engaged in similar tasks, or a convenient modelling abstraction. Components may contain variables, mathematical relationships that specify the interactions between those variables, and metadata. Variables may be local to a component, or made visible to other components via interface attributes. All interactions between variables within a component are described using MathML content markup. The interface attributes describe the external view of the component, specifying those variables visible to other components. A connection is a directed mapping from externally visible variables in one component to those of another. Every variable has a set of units associated with it, making it possible to connect together components with variables defined using different units. CellML offers additional facilities, such as metadata, for adding context information to a model, and component grouping. These assist in the creation and maintenance of models but do not alter the mathematics of the model. All models described using CellML can be reduced to the canonical form: a set of connected components.

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

Abstract: An essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.

What is flux balance analysis

Abstract: Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.

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

Abstract: 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. ∗ To whom correspondence should be addressed. Availability: The specification of SBML Level 1 is freely available from http://www.sbml.org/.

COPASI---a COmplex PAthway SImulator

Abstract: Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic--stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. Availability: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org. Contact: mendes@vbi.vt.edu

Large-scale gene function analysis with the PANTHER classification system

Abstract: The PANTHER (protein annotation through evolutionary relationship) classification system (http://wwwpantherdborg/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs) Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists In the 2013 release of PANTHER (v80), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system