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检索条件"主题词=Programming language"

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Making a Pangenome Using the Iterative Mapping Approach

Making a Pangenome Using the Iterative Mapping Approach

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作者： Cassandria Tay Fernandez

Pangenomes have replaced single reference genomes as genetic references, as they contain a better scope of the diversity found in a single species. This protocol outlines the iterative mapping approach in constructing a pangenome, including how to check the raw data, align the data to a reference, how to assemble the data, and how to remove potential contaminants from the final assembly. less

关键词： Bowtie Python programming language Bioinformatics Pangenome Plant genome Pangenomics Iterative mapping

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Species Tree Inference with SNP Data

Species Tree Inference with SNP Data

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作者： Michael Matschiner

While the inference of species trees from molecular sequences has become a common type of analysis in studies of species diversification, few programs so far allow for the use of single-nucleotide polymorphisms (SNPs) for the same purpose. In this book chapter, I discuss the use of the Bayesian program SNAPP, which infers the species tree by mathematically integrating over all possible genealogies at each SNP. In particular, I focus on a molecular clock model developed for SNAPP, allowing the inference of divergence times together with the species tree topology and the population size, directly from SNP datasets in variant call format. With the growing availability of SNP datasets for multiple closely related species, this approach is becoming increasingly relevant for the reconstruction of the temporal framework of recent species diversification. less

关键词： Genomics Statistical Calculation programming language Genotyping SNPs Phylogeny Species tree BEAST Divergence times SNAPP

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Analysis of Complex Circadian Time Series Data Using Wavelets

Analysis of Complex Circadian Time Series Data Using Wavelet...

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作者： Christoph Schmal Gregor Mönke Adrián E. Granada

Experiments that compare rhythmic properties across different genetic alterations and entrainment conditions underlie some of the most important breakthroughs in circadian biology. A robust estimation of the rhythmic properties of the circadian signals goes hand in hand with these discoveries. Widely applied traditional signal analysis methods such as fitting cosine functions or Fourier transformations rely on the assumption that oscillation periods do not change over time. However, novel high-resolution recording techniques have shown that, most commonly, circadian signals exhibit time-dependent changes of periods and amplitudes which cannot be captured with the traditional approaches. In this chapter we introduce a method to determine time-dependent properties of oscillatory signals, using the novel open-source Python-based Biological Oscillations Analysis Toolkit (pyBOAT). We show with examples how to detect rhythms, compute and interpret high-resolution time-dependent spectral results, analyze the main oscillatory component, and to subsequently determine these main components’ time-dependent instantaneous period, amplitude, and phase. We introduce step-by-step how such an analysis can be done by means of the easy-to-use point-and-click graphical user interface (GUI) provided by pyBOAT or executed within a Python programming environment. Concepts are explained using simulated signals as well as experimentally obtained time series. less

关键词： Data analysis Spectral Analysis Python Statistical Calculation programming language Cell And Tissue Culture Synchronization Circadian clocks Oscillations Time series analysis Wavelets Nonstationary signals

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Time-Resolved SANS to Measure Monomer Inter-Bilayer Exchange and Intra-Bilayer Translocation

Time-Resolved SANS to Measure Monomer Inter-Bilayer Exchange...

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作者： Michael H. Nguyen Mitchell DiPasquale Stuart R. Castillo Drew Marquardt

The monomeric exchange kinetics of sub-micron particles provide insight into their stability and dynamism. Traditional techniques used to measure the intra- and inter-particle exchange often require monitoring the transfer of bulky and perturbing fluorescent labels. Time-resolved small angle neutron scattering (TR-SANS) overcomes these flaws by isotope labeling, allowing for the monomeric exchange rate determination of unperturbed, stress-free particles. Here, we describe TR-SANS in detail and novel applications of the technique. less

关键词： Small-angle Neutron Scattering Isotope Labeling Extrusion Light Scattering NMR Small-angle X-ray Scattering (SAXS) Neutron Scattering Data analysis Python programming language Lipids Exchange Flip-flop SANS

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Text Mining Protocol to Retrieve Significant Drug–Gene Interactions from PubMed Abstracts

Text Mining Protocol to Retrieve Significant Drug–Gene Inte...

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作者： Sadhanha Anand Oviya Ramalakshmi Iyyappan Sharanya Manoharan Dheepa Anand Manonmani Alvin Jose Raja Ravi Shanker

Genes and proteins form the basis of all cellular processes and ensure a smooth functioning of the human system. The diseases caused in humans can be either genetic in nature or may be caused due to external factors. Genetic diseases are mainly the result of any anomaly in gene/protein structure or function. This disruption interferes with the normal expression of cellular components. Against external factors, even though the immunogenicity of every individual protects them to a certain extent from infections, they are still susceptible to other disease-causing agents. Understanding the biological pathway/entities that could be targeted by specific drugs is an essential component of drug discovery. The traditional drug target discovery process is time-consuming and practically not feasible. A computational approach could provide speed and efficiency to the method. With the presence of vast biomedical literature, text mining also seems to be an obvious choice which could efficiently aid with other computational methods in identifying drug–gene targets. These could aid in initial stages of reviewing the disease components or can even aid parallel in extracting drug–disease–gene/protein relationships from literature. The present chapter aims at finding drug–gene interactions and how the information could be explored for drug interaction. less

关键词： Text Mining programming language Python Natural language Processing Machine Learning Statistical Calculation Functional annotation Polymorphism ADR Drug–disease–target Drug–gene interaction

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geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO)

geneExpressionFromGEO: An R Package to Facilitate Data Readi...

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作者： Davide Chicco

Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in online databases and repositories, such as Gene Expression Omnibus (GEO). To read and analyze gene expression data, the computational biology community has developed several tools and platforms, including Bioconductor, an R open-source platform of software packages that can be used to analyze these data. Despite the usefulness of Bioconductor and of its packages, it is still difficult to read gene expression data from GEO, and to assign gene symbols to the probesets of datasets. To alleviate this problem, we introduce here a new R software package, geneExpressionFromGEO, which provides to the users the possibility to easily download gene expression data from GEO and to easily associate gene symbols to probesets. In this short chapter, we describe the assets of our software package, and we report an example of its usage. We believe that geneExpressionFromGEO can be very useful for the R community of bioinformaticians working on gene expression data. less

关键词： Microarray Gene Expression Profiling programming language Gene expression Bioconductor Gene Expression Omnibus

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Rules of Engagement: A Guide to Developing Agent-Based ModelsAgent-based models (ABM)

Rules of Engagement: A Guide to Developing Agent-Based Model...

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作者： Marc Griesemer Suzanne S. Sindi

Agent-based models (ABM), also called individual-based models, first appeared several decades ago with the promise of nearly real-time simulations of active, autonomous individuals such as animals or objects. The goal of ABMs is to represent a population of individuals (agents) interacting with one another and their environment. Because of their flexible framework, ABMs have been widely applied to study systems in engineering, economics, ecology, and biology. This chapter is intended to guide the users in the development of an agent-based model by discussing conceptual issues, implementation, and pitfalls of ABMs from first principles. As a case study, we consider an ABM of the multi-scale dynamics of cellular interactions in a microbial community. We develop a lattice-free agent-based model of individual cells whose actions of growth, movement, and division are influenced by both their individual processes (cell cycle) and their contact with other cells (adhesion and contact inhibition). less

关键词： Stochastic Simulation programming language Agent-based models Stochastic simulations Individual-based models Lattice-free

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Definition, Modeling, and Detection of Saccades in the Face of Post-saccadic Oscillations

Definition, Modeling, and Detection of Saccades in the Face ...

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作者： Richard Schweitzer Martin Rolfs

When analyzing eye tracking data, one of the central tasks is the detection of saccades. Although many automatic saccade detection algorithms exist, the field still debates how to deal with brief periods of instability around saccade offset, so-called post-saccadic oscillations (PSOs), which are especially prominent in today’s widely used video-based eye tracking techniques. There is good evidence that PSOs are caused by inertial forces that act on the elastic components of the eye, such as the iris or the lens. As this relative movement can greatly distort estimates of saccade metrics, especially saccade duration and peak velocity, video-based eye tracking has recurrently been considered unsuitable for measuring saccade kinematics. In this chapter, we review recent biophysical models that describe the relationship between pupil motion and eyeball motion. We found that these models were well capable of accurately reproducing saccade trajectories and we implemented a we framework for the simulation of saccades, PSOs, and fixations, which can be used—just like datasets hand-labeled by human experts—to evaluate detection algorithms and train statistical models. Moreover, as only pupil and corneal-reflection signals are observable in video-based eye tracking, one may also be able to use these models to predict the unobservable motion of the eyeball. Testing these predictions by analyzing saccade data that was registered with video-based and search-coil eye tracking techniques revealed strong relationships between the two types of measurements, especially when saccade offset is defined as the onset of the PSO. To enable eye tracking researchers to make use of this definition, we present and evaluate two novel algorithms: one based on eye movement direction inversion and one based on linear classifiers previously trained on simulation data. These algorithms allow for the detection of PSO onset with high fidelity. Even though PSOs may still pose problems for a range of eye

关键词： programming language Machine Learning Saccades Video-based eye tracking Post-saccadic oscillations Dynamic overshoots Saccade detection Modeling of saccade trajectories Scleral search coil Inertial forces Iris wobbling Saccade simulation Oculomotor control Eye movement

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Using Single-Molecule Fluorescence Microscopy to Uncover Neuronal Vulnerability to Protein Damage

Using Single-Molecule Fluorescence Microscopy to Uncover Neu...

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作者： Suleima Jacob-Tomas Lokha R. Alagar Boopathy Maria Vera

Neurodegenerative disorders (NDs) are diverse age-related conditions also described as “conformational diseases.” The hallmark of NDs is the accumulation of disease-specific proteins as toxic misfolded aggregates in some areas of the brain. They lead to the loss of protein homeostasis (proteostasis) that causes neuronal dysfunction and death. A potential therapeutic strategy for NDs is to prevent the accumulation of misfolded proteins by activating the heat shock response (HSR). The HSR maintains proteostasis through the upregulation of heat shock proteins (HSPs), molecular chaperones that recognize misfolded proteins, and either refold them to their functional conformations and/or target them for degradation. However, how to manipulate the expression of HSPs to obtain a therapeutic effect in neurons remains unclear. Furthermore, the regulation of the HSR in neurons is more complex than what we have learned from culturing somatic nonneuronal cells. This chapter describes a method to investigate the induction of HSP70 in primary hippocampal neurons using single-molecule fluorescence in situ hybridization (smFISH). Quantification of smFISH provides the means to analyze neuron-to-neuron variability in the activation of the HSR and enables us to study the transcriptional induction and localization of HSP70 mRNA in primary neurons. This information might be critical to find the druggable steps for developing effective therapies to treat age-related NDs. less

关键词： Single-molecule FISH Fluorescence Microscopy Immunofluorescence Python Neuronal Culture Cell And Tissue Culture Dissection Cross-linking Image Analysis Fiji MATLAB Data analysis Image Processing programming language Mus musculus Escherichia coli Lens Single-molecule imaging Neurodegenerative disorders Hippocampal neurons Heat shock response HSP70 mRNA Anti-GFAP Anti-rabbit Anti-mouse

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A Hybrid Protocol for Finding Novel Gene Targets for Various Diseases Using Microarray Expression Data Analysis and Text Mining

A Hybrid Protocol for Finding Novel Gene Targets for Various...

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作者： Sharanya Manoharan Oviya Ramalakshmi Iyyappan

The advancement in technology for various scientific experiments and the amount of raw data produced from that is enormous, thus giving rise to various subsets of biologists working with genome, proteome, transcriptome, expression, pathway, and so on. This has led to exponential growth in scientific literature which is becoming beyond the means of manual curation and annotation for extracting information of importance. Microarray data are expression data, analysis of which results in a set of up/downregulated lists of genes that are functionally annotated to ascertain the biological meaning of genes. These genes are represented as vocabularies and/or Gene Ontology terms when associated with pathway enrichment analysis need relational and conceptual understanding to a disease. The chapter deals with a hybrid approach we designed for identifying novel drug–disease targets. Microarray data for muscular dystrophy is explored here as an example and text mining approaches are utilized with an aim to identify promisingly novel drug targets. Our main objective is to give a basic overview from a biologist’s perspective for whom text mining approaches of data mining and information retrieval is fairly a new concept. The chapter aims to bridge the gap between biologist and computational text miners and bring about unison for a more informative research in a fast and time efficient manner. less

关键词： Text Mining Gene Prediction Gene Expression Analysis Microarray Data analysis Data Mining Ensembl programming language Pathway Or Network Visualization Statistical Calculation Cytoscape Gene function analysis Drug target Information extraction Gene enrichment Drug target prediction

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