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Application of miRNA-seq in neuropsychiatry: A methodological perspective

COMPUTERS IN BIOLOGY AND MEDICINE 2021年 135卷 104603-104603页

作者： Perez-Rodriguez, Daniel Lopez-Fernandez, Hugo Agis-Balboa, Roberto C. SERGAS UVIGO Galicia Sur Hlth Res Inst IIS Galicia Sur Hosp Alvaro Cunqueiro Translat Neurosci Grp CIBERSAMArea Sanitaria Vig Vigo 36213 Spain SERGAS UVIGO Univ Hosp Complex Vigo NeuroEpigenet Lab Vigo 36213 Spain Univ Porto Inst Invest & Inovacao Saude I3S Rua Alfredo Allen 208 P-4200135 Porto Portugal Univ Vigo Dept Comp Sci CINBIO ESEI Escuela Super Ingn Informat Orense 32004 Spain SERGAS UVIGO Galicia Sur Hlth Res Inst IIS Galicia Sur SING Res Grp Vigo Spain

MiRNAs are emerging as key molecules to study neuropsychiatric diseases. However, despite the large number of methodologies and software for miRNA-seq analyses, there is little supporting literature for researchers in this area. This review focuses on evaluating how miRNA-seq has been used to study neuropsychiatric diseases to date, analyzing both the main findings discovered and the bioinformatics workflows and tools used from a methodological perspective. The objective of this review is two-fold: first, to evaluate current miRNA-seq procedures used in neuropsychiatry;and second, to offer comprehensive information that can serve as a guide to new researchers in bioinformatics. After conducting a systematic search (from 2016 to June 30, 2020) of articles using miRNA-seq in neuropsychiatry, we have seen that it has already been used for different types of studies in three main categories: diagnosis, prognosis, and mechanism. We carefully analyzed the bioinformatics workflows of each study, observing a high degree of variability with respect to the tools and methods used and several methodological complexities that are identified and discussed in this review.

关键词： RNA-Seq microRNAs Neuropsychiatric diseases NGS bioinformatics workflow Guide

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UTAP: User-friendly Transcriptome Analysis Pipeline

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BMC bioinformatics 2019年第1期20卷 1-7页

作者： Kohen, Refael Barlev, Jonathan Hornung, Gil Stelzer, Gil Feldmesser, Ester Kogan, Kiril Safran, Marilyn Leshkowitz, Dena Weizmann Inst Sci Dept Life Sci Core Facil Bioinformat Unit IL-76100 Rehovot Israel Weizmann Inst Sci Mantoux Bioinformat Inst Nancy IL-76100 Rehovot Israel Weizmann Inst Sci Stephen Grand Israel Natl Ctr Personalized Med Dept Life Sci Core Facil IL-76100 Rehovot Israel

RNA-Seq technology is routinely used to characterize the transcriptome, and to detect gene expression differences among cell types, genotypes and conditions. Advances in short-read sequencing instruments such as Illumina Next-Seq have yielded easy-to-operate machines, with high throughput, at a lower price per base. However, processing this data requires bioinformatics expertise to tailor and execute specific solutions for each type of library preparation. In order to enable fast and user-friendly data analysis, we developed an intuitive and scalable transcriptome pipeline that executes the full process, starting from cDNA sequences derived by RNA-Seq [Nat Rev Genet 10:57-63, 2009] and bulk MARS-Seq [Science 343:776-779, 2014] and ending with sets of differentially expressed genes. Output files are placed in structured folders, and results summaries are provided in rich and comprehensive reports, containing dozens of plots, tables and links. Our User-friendly Transcriptome Analysis Pipeline (UTAP) is an open source, web-based intuitive platform available to the biomedical research community, enabling researchers to efficiently and accurately analyse transcriptome sequence data.

关键词： NGS Transcriptome RNA-Seq Sequence analysis pipeline bioinformatics workflow Differentially expressed genes Genome mapping Bulk MARS-Seq UMI (unique molecular identifier) Gene expression profile Normalization

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Barcoded sequencing workflow for high throughput digitization of hybridoma antibody variable domain sequences

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JOURNAL OF IMMUNOLOGICAL METHODS 2018年 455卷 88-94页

作者： Chen, Yongmei Kim, Si Hyun Shang, Yonglei Guillory, Joseph Stinson, Jeremy Zhang, Qing Hotzel, Isidro Hoi, Kam Hon Genentech Inc Dept Antibody Engn San Francisco CA 94080 USA Genentech Inc Dept Bioinformat & Computat Biol San Francisco CA 94080 USA Genentech Inc Dept Mol Biol San Francisco CA 94080 USA

Since the invention of Hybridoma technology by Milstein and Kohler in 1975, its application has greatly advanced the antibody discovery process. The technology enables both functional screening and long-term archival of the immortalized monoclonal antibody producing B cells. Despite the dependable cryopreservation technology for hybridoma cells, practicality of long-term storage has been outpaced by recent progress in robotics and automations, which enables routine identification of thousands of antigen specific hybridoma clones. Such throughput increase imposes two nascent challenges in the antibody discovery process, namely limited cryopreservation storage space and limited throughput in conventional antibody sequencing. We herein provide a barcoded sequencing workflow that utilizes next generation sequencing to expand the conventional sequencing capacity. Accompanied with the bioinformatics tools we describe, the barcoded sequencing workflow robustly reports unambiguous antibody sequences as confirmed with Sanger sequencing controls. In complement with the commonly accessible recombinant DNA technology, the barcoded sequencing workflow allows for high throughput digitization of the antibody sequences and provides an effective solution to the limitations imposed by physical storage and sequencing capacity.

关键词： Antibody sequencing Next Generation Sequencing Hybridoma sequencing bioinformatics workflow Barcoded primers 96-Well plate

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Recent computational developments on CLIP-seq data analysis and microRNA targeting implications

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BRIEFINGS IN bioinformatics 2018年第6期19卷 1290-1301页

作者： Bottini, Silvia Pratella, David Grandjean, Valerie Repetto, Emanuela Trabucchi, Michele INSERM Paris France Univ Cote Azur Nice France

Cross-Linking Immunoprecipitation associated to high-throughput sequencing (CLIP-seq) is a technique used to identify RNA directly bound to RNA-binding proteins across the entire transcriptome in cell or tissue samples. Recent technological and computational advances permit the analysis of many CLIP-seq samples simultaneously, allowing us to reveal the comprehensive network of RNA-protein interaction and to integrate it to other genome-wide analyses. Therefore, the design and quality management of the CLIP-seq analyses are of critical importance to extract clean and biological meaningful information from CLIP-seq experiments. The application of CLIP-seq technique to Argonaute 2 (Ago2) protein, the main component of the microRNA (miRNA)-induced silencing complex, reveals the direct binding sites of miRNAs, thus providing insightful information about the role played by miRNA(s). In this review, we summarize and discuss the most recent computational methods for CLIP-seq analysis, and discuss their impact on Ago2/miRNA-binding site identification and prediction with a regard toward human pathologies.

关键词： RNA immunoprecipitation bioinformatics workflow computational guideline large-scale analysis quality management microRNAs human pathologies

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A workflow for Predicting MicroRNAs Targets via Accessibility in Flavivirus Genomes 1

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11th Brazilian Symposium on bioinformatics (BSB)

作者： Valadares, Andressa Walter, Maria Emilia Raiol, Taina Univ Brasilia Inst Exact Sci Dept Comp Sci Brasilia DF Brazil Fundacao Oswaldo Cruz Fiocruz Brasilia Brasilia DF Brazil

ISBN: (数字)9783030017224

ISBN: (纸本)9783030017224;9783030017217

Flavivirus infections are a serious public health issue in Brazil, particularly in recent years due to the large number and severity of cases of Zika and Dengue virus infections and, more recently, outbreaks of Yellow Fever virus infections. Therefore, understanding the effects of genetic variations at functional and structural levels and developing new tools are necessary for supporting arboviral surveillance and control efforts of these viruses. In this context, we developed a workflow to predict potential microRNA targets in Flavivirus genomes. The workflow implementation comprised the integration of Perl scripts, tools from ViennaRNA package, and miRanda software to search for potential microRNAs that potentially interact with non-coding regions of Flavivirus genomes. As a case study, genome sequences of Dengue virus serotypes were used. We could observe structural differences among the serotype sequences and miRNA target binding sites exclusively identified for each serotype, which may be useful for the development of diagnostic methods.

关键词： Flavivirus Dengue microRNA RNA secondary structure bioinformatics workflow

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TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation

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BMC bioinformatics 2016年第1期17卷 1-11页

作者： Wolfien, Markus Rimmbach, Christian Schmitz, Ulf Jung, Julia Jeannine Krebs, Stefan Steinhoff, Gustav David, Robert Wolkenhauer, Olaf Univ Rostock Dept Syst Biol & Bioinformat D-18057 Rostock Germany Univ Rostock Reference & Translat Ctr Cardiac Stem Cell Therap D-18057 Rostock Germany Centenary Inst Gene & Stem Cell Therapy Program Camperdown NSW 2050 Australia Ludwig Maximilians Univ Munchen Gene Ctr Munich D-81377 Munich Germany Univ Stellenbosch Stellenbosch Inst Adv Study STIAS Wallenberg Res Ctr ZA-7602 Stellenbosch South Africa Univ Sydney Sydney Med Sch Sydney NSW 2006 Australia

Background: Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysis and interpretation of RNA sequencing data. We critically compare and evaluate state-of-the-art bioinformatics approaches and present a workflow that integrates the best performing data analysis, data evaluation and annotation methods in a Transparent, Reproducible and Automated PipeLINE (TRAPLINE) for RNA sequencing data processing (suitable for Illumina, SOLiD and Solexa). Results: Comparative transcriptomics analyses with TRAPLINE result in a set of differentially expressed genes, their corresponding protein-protein interactions, splice variants, promoter activity, predicted miRNA-target interactions and files for single nucleotide polymorphism (SNP) calling. The obtained results are combined into a single file for downstream analysis such as network construction. We demonstrate the value of the proposed pipeline by characterizing the transcriptome of our recently described stem cell derived antibiotic selected cardiac bodies ('aCaBs'). Conclusion: TRAPLINE supports NGS-based research by providing a workflow that requires no bioinformatics skills, decreases the processing time of the analysis and works in the cloud. The pipeline is implemented in the biomedical research platform Galaxy and is freely accessible via ***/RNAseqTRAPLINE or the specific Galaxy manual page (https://***/u/mwolfien/p/trapline-manual).

关键词： RNA sequencing NGS data processing Data evaluation bioinformatics workflow Galaxy TRAPLINE Stem cells

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bioinformatics Pipeline for Transcriptome Sequencing Analysis

Bioinformatics Pipeline for Transcriptome Sequencing Analysi...

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作者： Sarah Djebali Valentin Wucher Sylvain Foissac Christophe Hitte Erwan Corre Thomas Derrien

The development of High Throughput Sequencing (HTS) for RNA profiling (RNA-seq) has shed light on the diversity of transcriptomes. While RNA-seq is becoming a de facto standard for monitoring the population of expressed transcripts in a given condition at a specific time, processing the huge amount of data it generates requires dedicated bioinformatics programs. Here, we describe a standard bioinformatics protocol using state-of-the-art tools, the STAR mapper to align reads onto a reference genome, Cufflinks to reconstruct the transcriptome, and RSEM to quantify expression levels of genes and transcripts. We present the workflow using human transcriptome sequencing data from two biological replicates of the K562 cell line produced as part of the ENCODE3 project. less

关键词： RNA-seq High-Throughput Sequencing Transcription Profiling Cufflinks Statistical Calculation Genome Assembly Genome Annotation Transcriptome sequencing SAMtools Homo sapiens K-562 Protocols bioinformatics workflow

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Use of application containers and workflows for genomic data analysis

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Journal of Pathology Informatics 2016年第1期7卷 53-53页

作者： Schulz, Wade L. Durant, Thomas J. S. Siddon, Alexa J. Torres, Richard Department of Laboratory Medicine Yale University School of Medicine New Haven CT United States Pathology and Laboratory Medicine Service VA Connecticut Healthcare System West Haven CT United States

Background: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. Methods: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. Results: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data. Conclusions: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia. © 2016 Journal of Pathology Informatics | Published by Wolters Kluwer -Medknow.

关键词： Big data bioinformatics workflow containerization genomics

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Augmented Petri Net Cost Model for Optimisation of Large bioinformatics workflows Using Cloud

Augmented Petri Net Cost Model for Optimisation of Large Bio...

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UKSim-AMSS 7th European Modelling Symposium on Computer Modelling and Simulation (EMS)

作者： Xie, Zheng Han, Liangxiu Baldock, Richard Manchester Metropolitan Univ Sch Comp Math & Digital Technol Manchester M1 5GD Lancs England Univ Edinburgh Western Gen Hosp MRC Human Genet Unit MRC IGMM Edinburgh EH4 2XU Midlothian Scotland

ISBN: (纸本)9781479925780

This paper concerns the trade-off that may be made between the cost of storing intermediate data and the computing costs incurred in regenerating this data when large bioinformatics or other workflows are implemented using cloud resources. The implementation may be required to delete some data to keep storage costs within a budget, and deciding how best to do this with minimal increase in computing costs can cause complex problems. To address these problems, a modified form of Petri net is introduced for modeling the workflow and allowing an optimization algorithm to be applied for addressing several types of problem that may arise. The proposed 'augmented Petri-net' simulates workflows with cost models included, thus providing a platform for an optimization procedure. Illustrations are presented to show that such optimization can achieve overall cost reductions in a number of different scenarios.

关键词： Petri Net bioinformatics workflow Cloud cost model

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MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing

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BMC bioinformatics 2014年第1期15卷 1-11页

作者： Kalari, Krishna R. Nair, Asha A. Bhavsar, Jaysheel D. O'Brien, Daniel R. Davila, Jaime I. Bockol, Matthew A. Nie, Jinfu Tang, Xiaojia Baheti, Saurabh Doughty, Jay B. Middha, Sumit Sicotte, Hugues Thompson, Aubrey E. Asmann, Yan W. Kocher, Jean-Pierre A. Mayo Clin Dept Hlth Sci Res Rochester MN 55905 USA Mayo Clin Dept Canc Biol Jacksonville FL 32224 USA Mayo Clin Dept Hlth Sci Res Jacksonville FL 32224 USA

Background: Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome. Results: For optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients. Conclusions: Our software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://***/research/maprseq/.

关键词： Transcriptomic sequencing RNA-Seq bioinformatics workflow Gene expression Exon counts Fusion transcripts Expressed single nucleotide variants RNA-Seq reports

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