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检索条件"主题词=Programming Language"

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Computational Proteomics with Jupyter and Python

Computational Proteomics with Jupyter and Python

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作者： Lars Malmström

Proteomics based on mass spectrometry produces complex data in large quantities. The need for flexible computational pipelines, in the context of big data, in proteomics and other areas of science, has prompted the development of computational platforms and libraries that facilitate data analysis and data processing. In this respect, Python appears to be one of the winners among programming languages in terms of popularity and development. This chapter shows how to perform basic tasks using Python and dedicated libraries in a Jupyter framework: from basic search result summarizations to the creation of MS1 chromatograms. less

关键词： Proteomics Mass Spectrometry Machine Learning Python Data analysis programming language R Jupyter Reproducible research JupyterHub

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Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices

Predicting Post-Translational Modifications from Local Seque...

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作者： Marcin Tatjewski Marcin Kierczak Dariusz Plewczynski

Here, we present two perspectives on the task of predicting post translational modifications (PTMs) from local sequence fragments using machine learning algorithms. The first is the description of the fundamental steps required to construct a PTM predictor from the very beginning. These steps include data gathering, feature extraction, or machine-learning classifier selection. The second part of our work contains the detailed discussion of more advanced problems which are encountered in PTM prediction task. Probably the most challenging issues which we have covered here are: (1) how to address the training data class imbalance problem (we also present statistics describing the problem); (2) how to properly set up cross-validation folds with an approach which takes into account the homology of protein data records, to address this problem we present our folds-over-clusters algorithm; and (3) how to efficiently reach for new sources of learning features. Presented techniques and notes resulted from intense studies in the field, performed by our and other groups, and can be useful both for researchers beginning in the field of PTM prediction and for those who want to extend the repertoire of their research techniques. less

关键词： Machine Learning Position-Specific Scoring Matrices Protein Secondary Structure Decision Tree Neural Network Model Mass Spectrometry UniProtKB Statistical Calculation MATLAB programming language Python Feature selection Phosphorylation Feature extraction Cross-validation Class imbalance

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Accurate Detection of Differential Expression and Splicing Using Low-Level Features

Accurate Detection of Differential Expression and Splicing U...

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作者： Tomi Suomi Laura L. Elo

Gene expression can be quantified in high throughput using microarray technology. Here we describe how to accurately detect differential expression and splicing using a probe-level expression change averaging (PECA) method. PECA is available as an R package from Bioconductor (https://*** ), and it supports multiple operating systems. less

关键词： Gene Expression Analysis Splicing Model Analysis Microarray Differential Expression Analysis Data analysis programming language Homo sapiens Differential expression PECA Differential splicing Probe level

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High-Throughput Phenotyping of Plant Populations Using a Personal Digital Assistant

High-Throughput Phenotyping of Plant Populations Using a Per...

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作者： Raju Naik Vankudavath Reddaiah Bodanapu Yellamaraju Sreelakshmi Rameshwar Sharma

During many biological experiments voluminous data is acquired, which can be best collected with portable data acquisition devices and later analyzed with a personal computer (PC). Public domain software catering to data acquisition and analysis is currently limited. The necessity of phenotyping large plant populations led to the development of the application “PHENOME” to manage the data. PHENOME allows acquisition of phenotypic data using a personal digital assistant (PDA) with a built-in barcode scanner. The acquired data can be exported to a customized database on a PC for further analysis and cataloging. PHENOME can be used for a variety of applications, for example high-throughput phenotyping of a mutagenized or mapping population, or phenotyping of several individuals in one or more ecological niches. less

关键词： Functional Genomics programming language High-throughput phenotyping Computable phenotypic database Computer-aided data acquisition Personal digital assistant

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programming a multi-agent system with MASL

Programming a multi-agent system with MASL

引用

2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Pages 949-1423

作者： Dominique Duhaut Yann Le Guyadec Michel Dubois Valoria Universite de Bretagne Sud Lorient Vannes Morbihan France

ISBN: (纸本)9781424424948

Expressing the general behaviour of a set of robots working together is a difficult task. Self reconfigurable robots or a team of robots playing football are examples of such problem. To control a set of homogeneous or heterogeneous robotic components, one needs to express synchronous and asynchronous computation, from a local or a global point of view. In this paper we propose a unique language to express the behaviour of a set of heterogeneous robots.

关键词： multi-agent systems self-reconfigurable robots RoboCup programming language

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Simulating Crop Root Systems Using

Simulating Crop Root Systems Using

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作者： Ernst D. Schäfer Markus R. Owen Johannes A. Postma Christian Kuppe Christopher K. Black Jonathan P. Lynch

Functional–structural plant models are valuable modeling tools in analyzing plant development. A functional–structural plant model combines a three-dimensional representation of plant structure with models for physiological functions in order to better understand plant development. We present a guide to simulating crop root systems with OpenSimRoot, a feature-rich, highly cited, and open-source functional–structural root architecture model. We describe in detail how to create your own input files in conjunction with some examples. The aim of this guide is to highlight the potential of computational modeling in biology and to make modeling more accessible to the plant science community. less

关键词： Python programming language Plant development Nutrient uptake Modelling Organ growth Mathematical modelling Root system architectures

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Dynamic Clamp in Cardiac and Neuronal Systems Using RTXI

Dynamic Clamp in Cardiac and Neuronal Systems Using RTXI

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作者： Francis A. Ortega Robert J. Butera David J. Christini John A. White Alan D. Dorval

The injection of computer-simulated conductances through the dynamic clamp technique has allowed researchers to probe the intercellular and intracellular dynamics of cardiac and neuronal systems with great precision. By coupling computational models to biological systems, dynamic clamp has become a proven tool in electrophysiology with many applications, such as generating hybrid networks in neurons or simulating channelopathies in cardiomyocytes. While its applications are broad, the approach is straightforward: synthesizing traditional patch clamp, computational modeling, and closed-loop feedback control to simulate a cellular conductance. Here, we present two example applications: artificial blocking of the inward rectifier potassium current in a cardiomyocyte and coupling of a biological neuron to a virtual neuron through a virtual synapse. The design and implementation of the necessary software to administer these dynamic clamp experiments can be difficult. In this chapter, we provide an overview of designing and implementing a dynamic clamp experiment using the Real-Time eXperiment Interface (RTXI), an open-source software system tailored for real-time biological experiments. We present two ways to achieve this using RTXI’s modular format, through the creation of a custom user-made module and through existing modules found in RTXI’s online library. less

关键词： Electrophysiology Patch Clamp Technique Intraperitoneal Injection Microscopy programming language Pull-down Assay Dynamic clamp RTXI Neuronal networks Artificial conductance block Reciprocal neuronal coupling

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An Interdisciplinary Approach for Designing Kinetic Models of the Ras/MAPK Signaling Pathway

An Interdisciplinary Approach for Designing Kinetic Models o...

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作者： Marcelo S. Reis Vincent Noël Matheus H. Dias Layra L. Albuquerque Amanda S. Guimarães Lulu Wu Junior Barrera Hugo A. Armelin

We present in this article a methodology for designing kinetic models of molecular signaling networks, which was exemplarily applied for modeling one of the Ras/MAPK signaling pathways in the mouse Y1 adrenocortical cell line. The methodology is interdisciplinary, that is, it was developed in a way that both dry and wet lab teams worked together along the whole modeling process. less

关键词： Western Blot ELISA Cell And Tissue Culture Cell Lysis SDS-PAGE Simulated Annealing Python programming language Mus musculus Ras ERK MAPK Nonlinear optimization Ordinary differential equation Cell signaling pathways Differential-algebraic equation Model-fitting analysis Model simplification Anti-rabbit

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Exploring the RNA Editing Potential of RNA-Seq Data by ExpEdit

Exploring the RNA Editing Potential of RNA-Seq Data by ExpEd...

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作者： Mattia D’Antonio Ernesto Picardi Tiziana Castrignanò Anna Maria D’Erchia Graziano Pesole

Revealing the impact of A-to-I RNA editing in RNA-Seq experiments is relevant in humans because RNA editing can influence gene expression. In addition, its deregulation has been linked to a variety of human diseases. Exploiting the RNA editing potential in complete RNA-Seq datasets, however, is a challenging task. Indeed, no dedicated software is available, and sometimes deep computational skills and appropriate hardware resources are required. To explore the impact of known RNA editing events in massive transcriptome sequencing experiments, we developed the ExpEdit web service application. In the present work, we provide an overview of ExpEdit as well as methodologies to investigate known RNA editing in human RNA-Seq datasets. less

关键词： Deep Sequencing Genomics RNA-seq Illumina Sequencing Genome Alignment TopHat Bowtie Genome Assembly Statistical Calculation Transcriptome sequencing Python programming language SAMtools Homo sapiens Bioinformatics RNA editing A-to-I editing

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Simulating 3D Cell Shape with the Cellular Potts Model

Simulating 3D Cell Shape with the Cellular Potts Model

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作者： Rabea Link Ulrich S. Schwarz

Computer simulations have become a widely used method for the field of mechanobiology. An important question is whether one can predict the shape and forces of cells as a function of the extracellular environment. Different types of models have been described before to simulate cell and tissue shapes in structured environments. In this chapter, we give a brief overview of commonly used models and then describe the Cellular Potts Model, a lattice-based modelling framework, in more detail. We provide a hands-on guide on how to build a model that simulates the shape of a single cell on a micropattern in three dimensions in different open source software packages using the Cellular Potts framework. A simulation is set up with an initial configuration of generalized cells that change shape and position due to an energy function that incorporates cellular volume and surface area constraints as well as interaction energies between the generalized cells. less

关键词： Python programming language Cell Immobilization Cell adhesion Modelling Micropatterns Cell shape Cellular Potts model Computer simulations

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