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The discriminant power of RNA features for pre-miRNA recognition

BMC BIOINFORMATICS 2014年第1期15卷 1-11页

作者： Lopes, Ivani de O. N. Schliep, Alexander de Carvalho, Andre C. P. de L. F. Embrapa Soja Empresa Brasileira Pesquisa Agr BR-86001970 Londrina PR Brazil Rutgers State Univ Dept Comp Sci Piscataway NJ 08854 USA Rutgers State Univ BioMaPs Inst Quantitat Biol Piscataway NJ 08854 USA Inst Ciencias Matemat Comp Sao Carlos SP Brazil

Background: Computational discovery of microRNAs (miRNA) is based on pre-determined sets of features from miRNA precursors (pre-miRNA). Some feature sets are composed of sequence-structure patterns commonly found in pre-miRNAs, while others are a combination of more sophisticated RNA features. In this work, we analyze the discriminant power of seven feature sets, which are used in six pre-miRNA prediction tools. The analysis is based on the classification performance achieved with these feature sets for the training algorithms used in these tools. We also evaluate feature discrimination through the F-score and feature importance in the induction of random forests. Results: Small or non-significant differences were found among the estimated classification performances of classifiers induced using sets with diversification of features, despite the wide differences in their dimension. Inspired in these results, we obtained a lower-dimensional feature set, which achieved a sensitivity of 90% and a specificity of 95%. These estimates are within 0.1% of the maximal values obtained with any feature set (SELECT, Section "Results and discussion") while it is 34 times faster to compute. Even compared to another feature set (FS2, see Section "Results and discussion"), which is the computationally least expensive feature set of those from the literature which perform within 0.1% of the maximal values, it is 34 times faster to compute. The results obtained by the tools used as references in the experiments carried out showed that five out of these six tools have lower sensitivity or specificity. Conclusion: In miRNA discovery the number of putative miRNA loci is in the order of millions. Analysis of putative pre-miRNAs using a computationally expensive feature set would be wasteful or even unfeasible for large genomes. In this work, we propose a relatively inexpensive feature set and explore most of the learning aspects implemented in current ab-initio pre-miRNA prediction tools

关键词： Random Forest Classification Performance Predictive Performance python script Negative Sequence

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International chemical identifier for reactions (RInChI)

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JOURNAL OF CHEMINFORMATICS 2013年第1期5卷 1-9页

作者： Grethe, Guenter Goodman, Jonathan M. Allen, Chad H. G. Univ Cambridge Dept Chem Cambridge CB2 1EW England

The IUPAC International Chemical Identifier (InChI) provides a method to generate a unique text descriptor of molecular structures. Building on this work, we report a process to generate a unique text descriptor for reactions, RInChI. By carefully selecting the information that is included and by ordering the data carefully, different scientists studying the same reaction should produce the same RInChI. If differences arise, these are most likely the minor layers of the InChI, and so may be readily handled. RInChI provides a concise description of the key data in a chemical reaction, and will help enable the rapid searching and analysis of reaction databases.

关键词： Minor Layer python script Multistep Reaction Benzofuran Derivative Reaction Diagram

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An automated unit-cell modelling tool UnitCells© on Abaqus platform drawing functionalities from multiple external codes 19

An automated unit-cell modelling tool UnitCells© on Abaqus ...

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19th International Conference on Composite Materials, ICCM 2013

作者： Pan, Q. Yu, T. Jeanmeure, L. Li, S. Faculty of Engineering University of Nottingham University Park NottinghamNG7 2RD United Kingdom

This paper introduced an automatic unit cell modelling tool, UnitCells ©, based on Abaqus as a platform, drawing facilitating functions from various codes, including Texgen for generating textile configurations and Hypermesh for meshing. It is to create unit cells for various types of composite materials at micro and meso scales. Using Abaqus as a platform and its python script programming facility as a vehicle, a fully automated composites characterization tool has been achieved. Various effective material properties of composites can be readily obtained by using this tool. These properties are elastic properties, thermal expansion, thermal and electric conductivity. The characterisation process is fully controllable using embedded visual interfaces to define relevant geometric and material parameters. It can also be used for multi-scale modelling in the sense that different phases can be characterised in one length scale and fed into the analysis of another unit cell at a scale above. As a demonstration, some cases of unit cell model were analysed using this tool and presented in this paper. © QinetiQ Ltd 2013.

关键词： Characterisation Multi-scale modelling python script TCL script Unit cell

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STSE: Spatio-Temporal Simulation Environment Dedicated to Biology

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BMC BIOINFORMATICS 2011年第1期12卷 1-11页

作者： Stoma, Szymon Froehlich, Martina Gerber, Susanne Klipp, Edda Humboldt Univ Dept Theoret Biophys Berlin Germany USI Inst Computat Sci CH-6900 Lugano Switzerland

Background: Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. Results: The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e. g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (***) and can be downloaded from http://***/. The python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and w

关键词： Graphical User Interface python script Binary Mask Simulation Engine Polygonal Mesh

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FinFET Compact Modeling and Parameter Extraction

FinFET Compact Modeling and Parameter Extraction

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16th International Conference Mixed Design of Integrated Circuits and Systems

作者： Chevillon, Nicolas Tang, Mingchun Pregaldiny, Fabien Lallement, Christophe Madec, Morgan Univ Strasbourg InESS Strasbourg France

ISBN: (纸本)9788392875604

In this paper, we present a FinFET compact model and its associated parameter extraction methodology. This explicit model accounts for all major small geometry effects and allows accurate simulations of both n- and p-type FinFETs. The model core is physics-based (long-channel model) and some semiempirical corrections are introduced in order to accurately simulate the behavior of ultrashort (L = 25 nm) and ultrathin (W-Si =3 nm) FinFETs. The parameter extraction relies on a software suite allowing an automatic parameter extraction. In this work, the development of our parameter extraction procedure is based on 3-D simulation results. The optimization of parameters related to quantum effects, short-channel effects and channel length modulation illustrates the methodology of parameter extraction. Finally, we compare the FinFET characteristics (drain current and small signal parameters) obtained by our explicit compact model with 3-D numerical simulations for different Fin widths and channel lengths.

关键词： FinFET compact model parameter extraction optimization 3-D simulations Verilog-A python script short-channel effects quantum effects

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Declarative model description and code generation for hybrid individual- and population-based simulations of the early visual system

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BMC Neuroscience 2009年第1期10卷 1-2页

作者： Ralf Ansorg Lars Schwabe Department of Electrical Engineering and Computer Science Berlin University of Technology 10623 Berlin Germany Department of Computer Science and Electrical Engineering Adaptive and Regenerative Software Systems University of Rostock 18059 Rostock Germany

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STEPS: reaction-diffsion simulation in complex 3D geometries

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BMC Neuroscience 2009年第1期10卷 1-2页

作者： Iain Hepburn Erik De Schutter Stefan Wils Computational Neuroscience Unit Okinawa Institute of Science and Technology Okinawa 904-0411 Japan Theoretical Neurobiology University of Antwerp B-2610 Antwerpen Belgium

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Cinfony - combining Open Source cheminformatics toolkits behind a common interface

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CHEMISTRY CENTRAL JOURNAL 2008年第1期2卷 24-24页

作者： O'Boyle, Noel M. Hutchison, Geoffrey R. Cambridge Crystallog Data Ctr Cambridge CB2 1EZ England Univ Pittsburgh Dept Chem Chevron Sci Ctr Pittsburgh PA 15260 USA

Background: Open Source cheminformatics toolkits such as OpenBabel, the CDK and the RDKit share the same core functionality but support different sets of file formats and forcefields, and calculate different fingerprints and descriptors. Despite their complementary features, using these toolkits in the same program is difficult as they are implemented in different languages (C++ versus Java), have different underlying chemical models and have different application programming interfaces (APIs). Results: We describe Cinfony, a python module that presents a common interface to all three of these toolkits, allowing the user to easily combine methods and results from any of the toolkits. In general, the run time of the Cinfony modules is almost as fast as accessing the underlying toolkits directly from C++ or Java, but Cinfony makes it much easier to carry out common tasks in cheminformatics such as reading file formats and calculating descriptors. Conclusion: By providing a simplified interface and improving interoperability, Cinfony makes it easy to combine complementary features of OpenBabel, the CDK and the RDKit.

关键词： python script Java Virtual Machine Smile String Molecule Class Java Native Interface

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Vestige: Maximum likelihood phylogenetic footprinting

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BMC BIOINFORMATICS 2005年第1期6卷 130-130页

作者： Wakefield, MJ Maxwell, P Huttley, GA Australian Natl Univ John Curtin Sch Med Res Predict Med Grp Canberra ACT 0200 Australia Australian Natl Univ John Curtin Sch Med Res ARC Ctr Kangaroo Genom Canberra ACT 0200 Australia Australian Natl Univ John Curtin Sch Med Res Computat Genom Lab Canberra ACT 0200 Australia Australian Natl Univ John Curtin Sch Med Res Ctr Bioinformat Sci Canberra ACT 0200 Australia

Background: Phylogenetic footprinting is the identification of functional regions of DNA by their evolutionary conservation. This is achieved by comparing orthologous regions from multiple species and identifying the DNA regions that have diverged less than neutral DNA. Vestige is a phylogenetic footprinting package built on the PyEvolve toolkit that uses probabilistic molecular evolutionary modelling to represent aspects of sequence evolution, including the conventional divergence measure employed by other footprinting approaches. In addition to measuring the divergence, Vestige allows the expansion of the definition of a phylogenetic footprint to include variation in the distribution of any molecular evolutionary processes. This is achieved by displaying the distribution of model parameters that represent partitions of molecular evolutionary substitutions. Examination of the spatial incidence of these effects across regions of the genome can identify DNA segments that differ in the nature of the evolutionary process. Results: Vestige was applied to a reference dataset of the SCL locus from four species and provided clear identification of the known conserved regions in this dataset. To demonstrate the flexibility to use diverse models of molecular evolution and dissect the nature of the evolutionary process Vestige was used to footprint the Ka/Ks ratio in primate BRCA1 with a codon model of evolution. Two regions of putative adaptive evolution were identified illustrating the ability of Vestige to represent the spatial distribution of distinct molecular evolutionary processes. Conclusion: Vestige provides a flexible, open platform for phylogenetic footprinting. Underpinned by the PyEvolve toolkit, Vestige provides a framework for visualising the signatures of evolutionary processes across the genome of numerous organisms simultaneously. By exploiting the maximum-likelihood statistical framework, the complex interplay between mutational processes, DNA repair and se

关键词： Branch Length Additional Data File python script Phylogenetic Footprinting Motif Frequency

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PROVAT – a versatile tool for Voronoi tessellation analysis of protein structures and complexes

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BMC Bioinformatics 2005年第3期6卷 1-1页

作者： Swanand P Gore David F Burke Tom L Blundell Department of Biochemistry University of Cambridge UK

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