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Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery

Supervised Machine Learning with CITRUS for Single Cell Biom...

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作者： Hannah G. Polikowsky Katherine A. Drake

CITRUS is a supervised machine learning algorithm designed to analyze single cell data, identify cell populations, and identify changes in the frequencies or functional marker expression patterns of those populations that are significantly associated with an outcome. The algorithm is a black box that includes steps to cluster cell populations, characterize these populations, and identify the significant characteristics. This chapter describes how to optimize the use of CITRUS by combining it with upstream and downstream data analysis and visualization tools. less

关键词： Machine Learning Mass Cytometry Data analysis programming language Biomarker discovery viSNE CITRUS anti-bcr

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In Silico Oncology Drug Repositioning and Polypharmacology

In Silico Oncology Drug Repositioning and Polypharmacology

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作者： Feixiong Cheng

Network-aided in silico approaches have been widely used for prediction of drug-target interactions and evaluation of drug safety to increase the clinical efficiency and productivity during drug discovery and development. Here we review the advances and new progress in this field and summarize the translational applications of several new network-aided in silico approaches we developed recently. In addition, we describe the detailed protocols for a network-aided drug repositioning infrastructure for identification of new targets for old drugs, failed drugs in clinical trials, and new chemical entities. These state-of-the-art network-aided in silico approaches have been used for the discovery and development of broad-acting and targeted clinical therapies for various complex diseases, in particular for oncology drug repositioning. In this chapter, the described network-aided in silico protocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest. less

关键词： Genomics Transcriptomics Proteomics programming language Systems biology Targeted therapy Polypharmacology Systems pharmacology Drug repositioning Precision oncology Drug-target interactions Network-based inference Panomics

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Leveraging Big Data to Transform Drug Discovery

Leveraging Big Data to Transform Drug Discovery

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作者： Benjamin S. Glicksberg Li Li Rong Chen Joel Dudley Bin Chen

The surge of public disease and drug-related data availability has facilitated the application of computational methodologies to transform drug discovery. In the current chapter, we outline and detail the various resources and tools one can leverage in order to perform such analyses. We further describe in depth the in silico workflows of two recent studies that have identified possible novel indications of existing drugs. Lastly, we delve into the caveats and considerations of this process to enable other researchers to perform rigorous computational drug discovery experiments of their own. less

关键词： Differential Expression Analysis RNA-seq Biopsy Principal Component Analysis Immunohistochemistry Surgery Cell Proliferation Assay RNA Interference Proteomics Functional Genomics Cytoscape Microarray programming language Python Homo sapiens Mus musculus Bioinformatics Drug discovery Pharmacogenomics Big data Systems pharmacology Drug repurposing Drug repositioning Clinical informatics Electronic medical records Gene expression data

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Quantitative Modelling of the Waddington Epigenetic Landscape

Quantitative Modelling of the Waddington Epigenetic Landscap...

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作者： Atefeh Taherian Fard Mark A. Ragan

C.H. Waddington introduced the epigenetic landscape as a metaphor to represent cellular decision-making during development. Like a population of balls rolling down a rough hillside, developing cells follow specific trajectories (valleys) and eventually come to rest in one or another low-energy state that represents a mature cell type. Waddington depicted the topography of this landscape as determined by interactions among gene products, thereby connecting genotype to phenotype. In modern terms, each point on the landscape represents a state of the underlying genetic regulatory network, which in turn is described by a gene expression profile. In this chapter we demonstrate how the mathematical formalism of Hopfield networks can be used to model this epigenetic landscape. Hopfield networks are auto-associative artificial neural networks; input patterns are stored as attractors of the network and can be recalled from noisy or incomplete inputs. The resulting models capture the temporal dynamics of a gene regulatory network, yielding quantitative insight into cellular development and phenotype. less

关键词： Neural Network Model Principal Component Analysis Python programming language Gene regulatory network Energy landscape Attractor Waddington epigenetic landscape Hopfield network Quantitative model

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Mapping the

Mapping the

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作者： Daniel J. Nightingale Stephen G. Oliver Kathryn S. Lilley

The subcellular localization of proteins is a posttranslational modification of paramount importance. The ability to study subcellular and organelle proteomes improves our understanding of cellular homeostasis and cellular dynamics. In this chapter, we describe a protocol for the unbiased and high-throughput study of protein subcellular localization in the yeast Saccharomyces cerevisiae: hyperplexed localization of organelle proteins by isotope tagging (hyperLOPIT), which involves biochemical fractionation of Saccharomyces cerevisiae and high resolution mass spectrometry-based protein quantitation using TMT 10-plex isobaric tags. This protocol enables the determination of the subcellular localizations of thousands of proteins in parallel in a single experiment and thereby deep sampling and high-resolution mapping of the spatial proteome. less

关键词： Subcellular Fractionation Cell And Tissue Culture Solid-phase Extraction (SPE) Mass Spectrometry Localization Of Organelle Proteins By Isotope Tagging Fractionation Isobaric Mass Labeling Sonication BCA assay Western Blot Chromatography hyperLOPIT Spatial proteomics programming language Saccharomyces cerevisiae Protein localization Organelle Anti-Cox2p

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A Web Framework to Improve Computer programming Learning

A Web Framework to Improve Computer Programming Learning

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IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)

作者： Ortiz-Ortiz, Octavio Jimenez-Murillo, Jose A. Jimenez-Hernandez, Erendira M. Tecnol Nacl Mexico Technol Inst Morelia Morelia Michoacan Mexico Univ Nacl Autonoma Mexico Grad Sci & Engn Comp Mexico City DF Mexico

ISBN: (纸本)9781538659359

The subject of "Fundamentals of programming" is the one that has the highest index of failure within the block of subjects of the first semester in several engineering careers at the Technological Institute of Morelia, Mexico, what causes a high percentage in the abandonment of studies. In this paper, a computer tool that students can use to practice what is learned in the classroom wherever they are, at their own pace, individually or in a team, is presented. This software, which was carried out using Blended Learning, led to an improvement in the learning of programming. The results show an increase in the levels of motivation and in the students' learning (with an increase in their final grade), and a reduction in the dropout rate.

关键词： programming logical proposition algorithm programming language teaching learning flexible education

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Benchmarking Implementations of Term Rewriting and Pattern Matching in Algebraic, Functional, and Object-Oriented languages The 4th Rewrite Engines Competition 1

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12th International Workshop on Rewriting Logic and its Applications (WRLA)

作者： Garavel, Hubert Tabikh, Mohammad-Ali Arrada, Imad-Seddik Univ Grenoble Alpes INRIA CNRS LIG F-38000 Grenoble France

ISBN: (数字)9783319998404

ISBN: (纸本)9783319998404;9783319998398

Many specification and programming languages have adopted term rewriting and pattern matching as a key feature. However, implementation techniques and observed performance greatly vary across languages and tools. To provide for an objective comparison, we developed an open, experimental platform based upon the ideas of the three Rewrite Engines Competitions (2006, 2008, and 2010), which we significantly enhanced, extended, and automated. We used this platform to benchmark interpreters and compilers for a number of algebraic, functional, and object-oriented languages, and we report about the results obtained for CafeOBJ, Clean, Haskell, LNT, LOTOS, Maude, mCRL2, OCaml, Opal, Rascal, Scala, SML (MLton and SML-NJ), Stratego/XT, and Tom.

关键词： Abstract data type Algebraic specification Compiler Functional programming Interpreter Object-oriented programming programming language Specification language Term rewrite engine Term rewrite system

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Identifying Suitable Target Regions and Analyzing Off-Target Effects of Therapeutic Oligonucleotides

Identifying Suitable Target Regions and Analyzing Off-Target...

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作者： Lykke Pedersen Peter H. Hagedorn Troels Koch

Antisense oligonucleotides (AONs) that promote degradation of complementary RNA are being developed as therapeutics. Here, we describe a simple computational workflow for identification of the regions on an RNA that are suitable for targeting with such AONs. The workflow is based on the statistical programming language R, and the calculations and data processing can be carried out on a desktop computer. Our workflow integrates well-established data resources and RNA structure-prediction tools and can be modified easily and expanded as new resources become available. less

关键词： programming language Data analysis Ensembl Homo sapiens Felis catus Ribonuclease H Off-target effects Antisense oligonucleotides Computational prediction Target regions

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Three-Dimensional Thermodynamic Simulation of Condensin as a DNA-Based Translocase

Three-Dimensional Thermodynamic Simulation of Condensin as a...

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作者： Josh Lawrimore Yunyan He Gregory M. Forest Kerry Bloom

Chromatin dynamics and organization can be altered by condensin complexes. In turn, the molecular behavior of a condensin complex changes based on the tension of the substrate to which condensin is bound. This interplay between chromatin organization and condensin behavior demonstrates the need for tools that allows condensin complexes to be observed on a variety of chromatin organizations. We provide a method for simulating condensin complexes on a dynamic polymer substrate using the polymer dynamics simulator ChromoShake and the condensin simulator RotoStep. These simulations can be converted into simulated fluorescent images that are able to be directly compared to experimental images of condensin and fluorescently labeled chromatin. Our pipeline enables users to explore how changes in condensin behavior alters chromatin dynamics and vice versa while providing simulated image datasets that can be directly compared to experimental observations. less

关键词： Image Analysis MATLAB Fluorescence Labeling Image Processing Extrusion Python programming language Chromatin Condensin Polymer dynamics simulator Simulated fluorescent images ChromoShake RotoStep Microscope Simulator 2

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Using DeepLabCut for 3D markerless pose estimation across species and behaviors

Using DeepLabCut for 3D markerless pose estimation across sp...

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作者： Tanmay Nath Alexander Mathis An Chi Chen Amir Patel Matthias Bethge Mackenzie Weygandt Mathis

Noninvasive behavioral tracking of animals during experiments is critical to many scientific pursuits. Extracting the poses of animals without using markers is often essential to measuring behavioral effects in biomechanics, genetics, ethology, and neuroscience. However, extracting detailed poses without markers in dynamically changing backgrounds has been challenging. We recently introduced an open-source toolbox called DeepLabCut that builds on a state-of-the-art human pose-estimation algorithm to allow a user to train a deep neural network with limited training data to precisely track user-defined features that match human labeling accuracy. Here, we provide an updated toolbox, developed as a Python package, that includes new features such as graphical user interfaces (GUIs), performance improvements, and active-learning-based network refinement. We provide a step-by-step procedure for using DeepLabCut that guides the user in creating a tailored, reusable analysis pipeline with a graphical processing unit (GPU) in 1–12 h (depending on frame size). Additionally, we provide Docker environments and Jupyter Notebooks that can be run on cloud resources such as Google Colaboratory. less

关键词： Statistical Calculation MATLAB Deep learning Python programming language Mus musculus Software Behavioural methods Computational platforms and environments Learning algorithms

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