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检索条件"主题词=Programming language"

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TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform

TMT One-Stop Shop: From Reliable Sample Preparation to Compu...

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作者： Mehdi Mirzaei Dana Pascovici Jemma X. Wu Joel Chick Yunqi Wu Brett Cooke Paul Haynes Mark P. Molloy

In this chapter we describe the workflow we use for labeled quantitative proteomics analysis using tandem mass tags (TMT) starting with the sample preparation and ending with the multivariate analysis of the resulting data. We detail the step-by-step process from sample processing, labeling, fractionation, and data processing using Proteome Discoverer through to data analysis and interpretation in the context of a multi-run experiment. The final analysis and data interpretation rely on an R package we call TMTPrepPro, which are deployed on a local GenePattern server, and used for generating various outputs which are also outlined herein. less

关键词： Shotgun Proteomics Protein Extraction Liquid Chromatography-tandem Mass Spectrometry Liquid Chromatography (LC) Proteomics TMT Quantitation Fractionation Isobaric Mass Labeling BCA assay Solid-phase Extraction (SPE) HPLC Principal Component Analysis Data analysis programming language TMT Software workflow

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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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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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Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers

Computational Approaches for Mining GRO-Seq Data to Identify...

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作者： Anusha Nagari Shino Murakami Venkat S. Malladi W. Lee Kraus

Transcriptional enhancers are DNA regulatory elements that are bound by transcription factors and act to positively regulate the expression of nearby or distally located target genes. Enhancers have many features that have been discovered using genomic analyses. Recent studies have shown that active enhancers recruit RNA polymerase II (Pol II) and are transcribed, producing enhancer RNAs (eRNAs). GRO-seq, a method for identifying the location and orientation of all actively transcribing RNA polymerases across the genome, is a powerful approach for monitoring nascent enhancer transcription. Furthermore, the unique pattern of enhancer transcription can be used to identify enhancers in the absence of any information about the underlying transcription factors. Here, we describe the computational approaches required to identify and analyze active enhancers using GRO-seq data, including data pre-processing, alignment, and transcript calling. In addition, we describe protocols and computational pipelines for mining GRO-seq data to identify active enhancers, as well as known transcription factor binding sites that are transcribed. Furthermore, we discuss approaches for integrating GRO-seq-based enhancer data with other genomic data, including target gene expression and function. Finally, we describe molecular biology assays that can be used to confirm and explore further the function of enhancers that have been identified using genomic assays. Together, these approaches should allow the user to identify and explore the features and biological functions of new cell type-specific enhancers. less

关键词： GRO-seq Statistical Calculation Genome Visualization DNase-Seq High-Throughput Sequencing Genomics Cutadapt Trimmomatic Data analysis SAMtools bedtools programming language Python Transcription Gene regulation Motif search Promoter Transcription factor Enhancer Motif Response element groHMM Enhancer RNAs (eRNAs) Enhancer prediction Looping Transcription unit

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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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SCENIC: single-cell regulatory network inference and clustering

SCENIC: single-cell regulatory network inference and cluster...

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作者： Sara Aibar Carmen Bravo González-Blas Thomas Moerman Vân Anh Huynh-Thu Hana Imrichova Gert Hulselmans Florian Rambow Jean-Christophe Marine Pierre Geurts Jan Aerts Joost van den Oord Zeynep Kalender Atak Jasper Wouters Stein Aerts

We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://*** ). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity. less

关键词： RNA-seq Transcriptomics Immunohistochemistry Cell And Tissue Culture Single-cell RNA-seq Surgery Python programming language Drop-seq Gene regulatory networks Tumour heterogeneity

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Bioinformatics Analysis of the Receptor-Like Kinase (RLK) Superfamily

Bioinformatics Analysis of the Receptor-Like Kinase (RLK) Su...

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作者： Otávio J. Brustolini José Cleydson Silva Tetsu Sakamoto Elizabeth P. Fontes

Receptor-like kinases (RLKs) play key roles during development and in responses to the environment. In plant immunity, some members of RLKs function as pattern recognition receptors (PRRs), which, upon recognition of pathogen-associated molecular patterns (PAMP), are recruited into active complexes to induce pathogen-triggered immunity (PTI). In this chapter, we describe the bioinformatics tools and procedures for the identification and phylogenetic classification of RLKs from different plant species as a framework for understanding RLK function in signal transduction and immunity. less

关键词： Genomics Phylogenetics Ensembl programming language Arabidopsis thaliana Homo sapiens Ectodomain Receptor-like kinase (RLK) Leucine-rich repeat (LRR) Serine/threonine kinase domain Pattern recognition receptors (PRR)

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Development of a Computational Approach/Model to Explore NMDA Receptors Functions

Development of a Computational Approach/Model to Explore NMD...

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作者： A. Florence Keller Jean-Marie C. Bouteiller Theodore W. Berger

Modern laboratory techniques allow studying NMDA receptors (NMDAR) either anatomically with specific antibodies coupled to sophisticated confocal microscopy, or physiologically by live imaging or electrophysiological techniques. However, NMDARs are not fixed in time and space and changes in their composition and/or distribution on the post-synaptic membrane may significantly impact the synaptic strength and overall function. The computational modeling approach therefore constitutes a complementary tool for investigating the properties of biological systems based on the knowledge provided by the lab experiments. Here, we describe a general computational method aiming at developing kinetic Markov-chain based models of NMDARs subtypes capable of reproducing various experimental results. These models are then used to make predictions on additional (non-obvious) properties and on their role in synaptic function under various physiological and pharmacological conditions. For the purpose of this book chapter, we will focus on the method used to develop a NMDAR model that includes pharmacological site of action of different compounds. Notably, this elementary model can subsequently be included in a neuron model (not described in detail here) to explore the impact of their differential distribution on synaptic functions. less

关键词： Confocal Microscopy Live Cell Imaging Data Mining Data analysis programming language Python Pharmacology Computational model Ordinary differential equation kinetic models NMDA receptors model Synaptic function Optimization algorithm

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Mathematical Modeling of Synaptic Patterns

Mathematical Modeling of Synaptic Patterns

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作者： Anastasios Siokis Philippe A. Robert Michael Meyer-Hermann

During antigen recognition by T cells, a specific spatial structure is formed at the contact face to an antigen-presenting cell (APC), called an immunological synapse (IS). The IS supports bidirectional signaling and release of effector molecules and is widely studied both biologically and numerically, in order to understand the process of T cell activation and signaling. This specialized structure harbors a central area (central supramolecular activation cluster, cSMAC) populated by T cell receptor-peptide-major histocompatibility complex (TCR-pMHC ) interactions, hedged by a peripheral ring (peripheral supramolecular activation cluster, pSMAC) of integrin lymphocyte function associated-1 interactions with its immunoglobulin superfamily ligand intercellular adhesion molecule-1 (LFA-1-ICAM-1). These two regions form the “bull’s eye” pattern characteristic of the mature IS. In theoretical studies, different modeling architectures, including partial differential equations (PDE) and agent-based modelsagent-based modeling , have been developed with the purpose to answer mechanistic questions about the IS dynamics. In this chapter, we explain possible physiological mechanisms that lead to the formation of ISs and technical issues that may occur in the course of development of agent-based models. less

关键词： Mathematical Modeling Cross-linking Fluorescence Microscopy programming language Computational biology Immunological synapse Agent-based modeling Patterns Partial differential equations (PDEs) Mechanics

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High-speed fixed-target serial virus crystallography

High-speed fixed-target serial virus crystallography

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作者： Philip Roedig Helen M Ginn Tim Pakendorf Geoff Sutton Karl Harlos Thomas S Walter Jan Meyer Pontus Fischer Ramona Duman Ismo Vartiainen Bernd Reime Martin Warmer Aaron S Brewster Iris D Young Tara Michels-Clark Nicholas K Sauter Abhay Kotecha James Kelly David J Rowlands Marcin Sikorsky Silke Nelson Daniel S Damiani Roberto Alonso-Mori Jingshan Ren Elizabeth E Fry Christian David David I Stuart Armin Wagner Alke Meents

We report a method for serial X-ray crystallography at X-ray free-electron lasers (XFELs), which allows for full use of the current 120-Hz repetition rate of the Linear Coherent Light Source (LCLS). Using a micropatterned silicon chip in combination with the high-speed Roadrunner goniometer for sample delivery, we were able to determine the crystal structures of the picornavirus bovine enterovirus 2 (BEV2) and the cytoplasmic polyhedrosis virus type 18 polyhedrin, with total data collection times of less than 14 and 10 min, respectively. Our method requires only micrograms of sample and should therefore broaden the applicability of serial femtosecond crystallography to challenging projects for which only limited sample amounts are available. By synchronizing the sample exchange to the XFEL repetition rate, our method allows for most efficient use of the limited beam time available at XFELs and should enable a substantial increase in sample throughput at these facilities. less

关键词： Nanocrystallography Statistical Calculation X-ray Crystallography Ultracentrifugation Lithography Macromolecular Crystallography serial femtosecond crystallography Python programming language Virology Proteins

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