Fluorescence in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotid...
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Fluorescence in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotide (oligo)-based FISH methods that have enabled researchers to study the three-dimensional organization of the genome at super-resolution and visualize the spatial patterns of gene expression for thousands of genes in individual cells. However, there are few existing computational tools to support the bioinformatics workflows necessary to carry out these experiments using oligo FISH probes. Here, we introduce paint server and homology optimization pipeline (PaintSHOP), an interactive platform for the design of oligo FISH experiments. PaintSHOP enables researchers to identify probes for their experimental targets efficiently, to incorporate additional necessary sequences such as primer pairs and to easily generate files documenting library design. PaintSHOP democratizes and standardizes the process of designing complex probe sets for the oligo FISH community. less
The expected dramatic growth of connected things raises the issue of how to efficiently organize them, in order to monitor and manage functions and interactions. Information centric networking (ICN) is a communication...
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The expected dramatic growth of connected things raises the issue of how to efficiently organize them, in order to monitor and manage functions and interactions. Information centric networking (ICN) is a communication paradigm that provides content-oriented functionality in the network and at the network level, including content routing, caching, multicast, mobility, data-centric security, and a flexible namespace. Thus, it is a viable solution for supporting Internet of Things (IoT) services without requiring any centralized entity. In this paper, we introduce the lightweight named object solution: a convenient way to represent physical IoT objects in a derived name space, exploiting ICN. We show that this abstraction can: 1) increase the programming simplicity;2) offer extended functionality, such as augmentation and upgrading, to cope with the "software erosion," and 3) implement a common interaction logic involving mutual function invocation. We present some proof-of-concept implementations of the proposed abstraction dealing with challenging IoT test cases;we also carry out a performance evaluation in a simulated network scenario.
Operational semantics is a known and popular semantic method for describing the execution of programs in detail. The traditional definition of this method defines each step of a program as a transition relation. We pr...
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Operational semantics is a known and popular semantic method for describing the execution of programs in detail. The traditional definition of this method defines each step of a program as a transition relation. We present a new approach on how to define operational semantics as a coalgebra over a category of configurations. Our approach enables us to deal with a program that is written in a small but real imperative language containing also the common program constructs as input and output statements, and declarations. A coalgebra enables to define operational semantics in a uniform way and it describes the behavior of the programs. The state space of our coalgebra consists of the configurations modeling the actual states;the morphisms in a base category of the coalgebra are the functions defining particular steps during the program's executions. Polynomial endofunctor determines this type of systems. Another advantage of our approach is its easy implementation and graphical representation, which we illustrate on a simple program.
ChIP-seq is the method of choice for profiling protein–DNA interactions, and notably for characterizing the landscape of transcription factor binding and histone modifications. This technique has been widely used to ...
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ChIP-seq is the method of choice for profiling protein–DNA interactions, and notably for characterizing the landscape of transcription factor binding and histone modifications. This technique has been widely used to study numerous aspects of tumor biology and led to the development of several promising cancer therapies. In Ewing sarcoma research, ChIP-seq provided important insights into the mechanism of action of the major oncogenic fusion protein EWSR1-FLI1 and related epigenetic and transcriptional changes. In this chapter, we provide a detailed pipeline to analyze ChIP-seq experiments from the preprocessing of raw data to tertiary analysis of detected binding sites. We also advise on best practice to prepare tumor samples prior to sequencing. less
Multiphoton microscopy has become a powerful tool with which to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. However, tissue scattering, optical aberrations and mot...
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Multiphoton microscopy has become a powerful tool with which to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. However, tissue scattering, optical aberrations and motion artifacts degrade the imaging performance at depth. Here we describe a minimally invasive intravital imaging methodology based on three-photon excitation, indirect adaptive optics (AO) and active electrocardiogram gating to advance deep-tissue imaging. Our modal-based, sensorless AO approach is robust to low signal-to-noise ratios as commonly encountered in deep scattering tissues such as the mouse brain, and permits AO correction over large axial fields of view. We demonstrate near-diffraction-limited imaging of deep cortical spines and (sub)cortical dendrites up to a depth of 1.4 mm (the edge of the mouse CA1 hippocampus). In addition, we show applications to deep-layer calcium imaging of astrocytes, including fibrous astrocytes that reside in the highly scattering corpus callosum. less
Whole-genome bisulfite sequencing (WGBS) is a popular method for characterizing cytosine methylation because it is fully quantitative and has base-pair resolution. While WGBS is prohibitively expensive for experiments...
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Whole-genome bisulfite sequencing (WGBS) is a popular method for characterizing cytosine methylation because it is fully quantitative and has base-pair resolution. While WGBS is prohibitively expensive for experiments involving many samples, low-coverage WGBS can accurately determine global methylation and erasure at similar cost to high-performance liquid chromatography (HPLC) or enzyme-linked immunosorbent assays (ELISA). Moreover, low-coverage WGBS has the capacity to distinguish between methylation in different cytosine contexts (e.g., CG, CHH, and CHG), can tolerate low-input material (<100 cells), and can detect the presence of overrepresented DNA originating from mitochondria or amplified ribosomal DNA. In addition to describing a WGBS library construction and quantitation approach, here we detail computational methods to predict the accuracy of low-coverage WGBS using empirical bootstrap samplers and theoretical estimators similar to those used in election polling. Using examples, we further demonstrate how non-independent sampling of cytosines can alter the precision of error calculation and provide methods to improve this. less
Bioinformatics programs have been developed that exploit informative signals encoded within protein sequences to predict protein characteristics. Unfortunately, there is no program as yet that can predict whether a pr...
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Bioinformatics programs have been developed that exploit informative signals encoded within protein sequences to predict protein characteristics. Unfortunately, there is no program as yet that can predict whether a protein will induce a protective immune response to a pathogen. Nonetheless, predicting those pathogen proteins most likely from those least likely to induce an immune response is feasible when collectively using predicted protein characteristics. Vacceed is a computational pipeline that manages different standalone bioinformatics programs to predict various protein characteristics, which offer supporting evidence on whether a protein is secreted or membrane -associated. A set of machine learning algorithms predicts the most likely pathogen proteins to induce an immune response given the supporting evidence. This chapter provides step by step descriptions of how to configure and operate Vacceed for a eukaryotic pathogen of the user’s choice. less
Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools...
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Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful. less
A method based on reversed phase high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (RP-HPLC-ESI-HRMS) for the comprehensive and reliable detection of seconda...
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A method based on reversed phase high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (RP-HPLC-ESI-HRMS) for the comprehensive and reliable detection of secondary metabolites of Trichoderma reesei cultured in synthetic minimal liquid medium is presented. A stable isotope-assisted (SIA) workflow is used, which allows the automated, comprehensive extraction of truly fungal metabolite-derived LC-MS signals from the acquired chromatographic data. The subsequent statistical data analysis and a typical outcome of such a metabolomics data evaluation are shown by way of example in a previously published study on the influence of the pleiotropic regulator transcription factor Xylanase promoter binding protein 1 (Xpp1) in T. reesei on secondary metabolism. less
Currently, the interactions occurring between oligonucleotides and the cellular envelope of bacteria are not fully resolved at the molecular level. Understanding these interactions is essential to gain insights on how...
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Currently, the interactions occurring between oligonucleotides and the cellular envelope of bacteria are not fully resolved at the molecular level. Understanding these interactions is essential to gain insights on how to improve the internalization of the tagged oligonucleotides during fluorescence in situ hybridization (FISH). Agent-based modeling (ABM) is a promising in silico tool to dynamically simulate FISH and bring forward new knowledge on this process. Notably, it is important to simulate the whole bacterial cell, including the different layers of the cell envelope, given that the oligonucleotide must cross the envelope to reach its target in the cytosol. In addition, it is also important to characterize other molecules in the cell to best emulate the cell and represent molecular crowding. Here, we review the main information that should be compiled to construct an ABM on FISH and provide a practical example of an oligonucleotide targeting the 23S rRNA of Escherichia coliEscherichia coli. less
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