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Alan Rubin https://linux.conf.au/schedule/30300/view_talk http://afrubin.github.io/miniconf/

In the rapidly evolving domain of next generation sequencing and bioinformatics analysis, data generation is one aspect that is increasing at a concomitant rate. The burden associated with processing large amounts of sequencing data has emphasised the need to allocate sufficient computing resources to complete analyses in the shortest possible time with manageable and predictable costs. A novel method for predicting time to completion for a popular bioinformatics software (QIIME), was developed using key variables characteristic of the input data assumed to impact processing time. Multiple Linear Regression models were developed to determine run time for two denoising algorithms and a general bioinformatics pipeline. The models were able to accurately predict clock time for denoising sequences from a naturally assembled community dataset, but not an artificial community. Speedup and efficiency tests for AmpliconNoise also highlighted that caution was needed when allocating resources for parallel processing of data. Accurate modelling of computational processing time using easily measurable predictors can assist NGS analysts in determining resource requirements for bioinformatics software and pipelines. Whilst demonstrated on a specific group of scripts, the methodology can be extended to encompass other packages running on multiple architectures, either in parallel or sequentially.

This article is from Asia Pacific Allergy , volume 1 . Abstract Bioinformatics, the study of integrating high throughput biological data and statistical model through intensive computation, has been attracting great interest in recent times and Sequencing is at the very center of it. The large amount of information obtained from sequencing has deepened our understanding and fundamental knowledge of organisms. This review will aim to provide a brief summary of new sequencing technology, current issues, and projects focused on medical applications. The article is organized in three parts. Part I explains common terminologies and background of sequencing technology, and Part II compares distinct features of currently available platforms. Part III contains applications in various medical fields.

This article is from Asia Pacific Allergy , volume 1 . Abstract Bioinformatics, the study of integrating high throughput biological data and statistical model through intensive computation, has been attracting great interest in recent times and Sequencing is at the very center of it. The large amount of information obtained from sequencing has deepened our understanding and fundamental knowledge of organisms. This review will aim to provide a brief summary of new sequencing technology, current issues, and projects focused on medical applications. The article is organized in three parts. Part I explains common terminologies and background of sequencing technology, and Part II compares distinct features of currently available platforms. Part III contains applications in various medical fields.

This article is from Asia Pacific Allergy , volume 1 . Abstract Bioinformatics, the study of integrating high throughput biological data and statistical model through intensive computation, has been attracting great interest in recent times and Sequencing is at the very center of it. The large amount of information obtained from sequencing has deepened our understanding and fundamental knowledge of organisms. This review will aim to provide a brief summary of new sequencing technology, current issues, and projects focused on medical applications. The article is organized in three parts. Part I explains common terminologies and background of sequencing technology, and Part II compares distinct features of currently available platforms. Part III contains applications in various medical fields.

This article is from Nucleic Acids Research , volume 42 . Abstract Molecular Biology has been at the heart of the ‘big data’ revolution from its very beginning, and the need for access to biological data is a common thread running from the 1965 publication of Dayhoff’s ‘Atlas of Protein Sequence and Structure’ through the Human Genome Project in the late 1990s and early 2000s to today’s population-scale sequencing initiatives. The European Bioinformatics Institute (EMBL-EBI; http://www.ebi.ac.uk) is one of three organizations worldwide that provides free access to comprehensive, integrated molecular data sets. Here, we summarize the principles underpinning the development of these public resources and provide an overview of EMBL-EBI’s database collection to complement the reviews of individual databases provided elsewhere in this issue.

Bioinformatics Books 2005 看看 生信算法讲义 CN

This article is from PLoS ONE , volume 9 . Abstract DNA methylation, one of the most important epigenetic modifications, plays a crucial role in various biological processes. The level of DNA methylation can be measured using whole-genome bisulfite sequencing at single base resolution. However, until now, there is a paucity of publicly available software for carrying out integrated methylation data analysis. In this study, we implemented Methy-Pipe, which not only fulfills the core data analysis requirements (e.g. sequence alignment, differential methylation analysis, etc.) but also provides useful tools for methylation data annotation and visualization. Specifically, it uses Burrow-Wheeler Transform (BWT) algorithm to directly align bisulfite sequencing reads to a reference genome and implements a novel sliding window based approach with statistical methods for the identification of differentially methylated regions (DMRs). The capability of processing data parallelly allows it to outperform a number of other bisulfite alignment software packages. To demonstrate its utility and performance, we applied it to both real and simulated bisulfite sequencing datasets. The results indicate that Methy-Pipe can accurately estimate methylation densities, identify DMRs and provide a variety of utility programs for downstream methylation data analysis. In summary, Methy-Pipe is a useful pipeline that can process whole genome bisulfite sequencing data in an efficient, accurate, and user-friendly manner. Software and test dataset are available at http://sunlab.lihs.cuhk.edu.hk/methy-pipe/.

This article is from PLoS ONE , volume 9 . Abstract DNA methylation, one of the most important epigenetic modifications, plays a crucial role in various biological processes. The level of DNA methylation can be measured using whole-genome bisulfite sequencing at single base resolution. However, until now, there is a paucity of publicly available software for carrying out integrated methylation data analysis. In this study, we implemented Methy-Pipe, which not only fulfills the core data analysis requirements (e.g. sequence alignment, differential methylation analysis, etc.) but also provides useful tools for methylation data annotation and visualization. Specifically, it uses Burrow-Wheeler Transform (BWT) algorithm to directly align bisulfite sequencing reads to a reference genome and implements a novel sliding window based approach with statistical methods for the identification of differentially methylated regions (DMRs). The capability of processing data parallelly allows it to outperform a number of other bisulfite alignment software packages. To demonstrate its utility and performance, we applied it to both real and simulated bisulfite sequencing datasets. The results indicate that Methy-Pipe can accurately estimate methylation densities, identify DMRs and provide a variety of utility programs for downstream methylation data analysis. In summary, Methy-Pipe is a useful pipeline that can process whole genome bisulfite sequencing data in an efficient, accurate, and user-friendly manner. Software and test dataset are available at http://sunlab.lihs.cuhk.edu.hk/methy-pipe/.

This article is from PLoS ONE , volume 9 . Abstract DNA methylation, one of the most important epigenetic modifications, plays a crucial role in various biological processes. The level of DNA methylation can be measured using whole-genome bisulfite sequencing at single base resolution. However, until now, there is a paucity of publicly available software for carrying out integrated methylation data analysis. In this study, we implemented Methy-Pipe, which not only fulfills the core data analysis requirements (e.g. sequence alignment, differential methylation analysis, etc.) but also provides useful tools for methylation data annotation and visualization. Specifically, it uses Burrow-Wheeler Transform (BWT) algorithm to directly align bisulfite sequencing reads to a reference genome and implements a novel sliding window based approach with statistical methods for the identification of differentially methylated regions (DMRs). The capability of processing data parallelly allows it to outperform a number of other bisulfite alignment software packages. To demonstrate its utility and performance, we applied it to both real and simulated bisulfite sequencing datasets. The results indicate that Methy-Pipe can accurately estimate methylation densities, identify DMRs and provide a variety of utility programs for downstream methylation data analysis. In summary, Methy-Pipe is a useful pipeline that can process whole genome bisulfite sequencing data in an efficient, accurate, and user-friendly manner. Software and test dataset are available at http://sunlab.lihs.cuhk.edu.hk/methy-pipe/.

3rd_CIBEC_Bioinformatics_PDFs

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

HLA-E gene from MHC (Major Histocompatibility Complex) system has been recently discovered, in our laboratory, in Invertebrates. Blasts were performed against different protein species to find or not homologies. Results were given in the precedent communication. 

Rex A. Dwyer Genomic Perl From Bioinformatics Basics To Working Code Cambridge University Press ( 2002) 2

The molecular mechanism of Glioma is still unclear, and there are few early diagnostic markers. Therefore, it is urgent to figure out effective preventive measures, active diagnostic methods and rapid treatment measures. In recent years, relevant studies have revealed that long non-coding RNA (lncRNA) is associated with the prognosis of Glioma. However, these results have not been supported by any evidence. Therefore, this study carried out a meta-analysis method to analyze the relationship between lncRNA and the prognosis of Glioma. In addition, bioinformatics analysis was conducted to investigate the mechanism and related pathways of lncRNAs in Glioma.

The function of Angipoietin-2 (Agn2) in osteosarcoma has not been fully explored and exists controversial. Therefore, we conducted a meta-analysis to investigate the role of Agn2 in the prognosis of osteosarcoma. In addition, bioinformatics analysis was carried out to reveal the mechanism and related pathways of Agn2 in osteosarcoma.

This article is from BMC Systems Biology , volume 7 . Abstract Background: In order to develop hypothesis on unknown metabolic pathways, biochemists frequently rely on literature that uses a free-text format to describe functional groups or substructures. In computational chemistry or cheminformatics, molecules are typically represented by chemical descriptors, i.e., vectors that summarize information on its various properties. However, it is difficult to interpret these chemical descriptors since they are not directly linked to the terminology of functional groups or substructures that the biochemists use. Methods: In this study, we used KEGG Chemical Function (KCF) format to computationally describe biochemical substructures in seven attributes that resemble biochemists' way of dealing with substructures. Results: We established KCF-S (KCF-and-Substructures) format as an additional structural information of KCF. Applying KCF-S revealed the specific appearance of substructures from various datasets of molecules that describes the characteristics of the respective datasets. Structure-based clustering of molecules using KCF-S resulted the clusters in which molecular weights and structures were less diverse than those obtained by conventional chemical fingerprints. We further applied KCF-S to find the pairs of molecules that are possibly converted to each other in enzymatic reactions, and KCF-S clearly improved predictive performance than that presented previously. Conclusions: KCF-S defines biochemical substructures with keeping interpretability, suggesting the potential to apply more studies on chemical bioinformatics. KCF and KCF-S can be automatically converted from Molfile format, enabling to deal with molecules from any data sources.

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As an anticancer gene, microRNA-145 (miRNA-145) inhibits the growth, migration and invasion of cancer cells, and inhibits tumorigenesis by targeting various genes that are abnormally expressed in tumors. However, whether miRNA-145 can be applied as a biomarker for potential prognosis of ovarian cancer still remains controversial. Therefore, this study further explored the prognostic value and mechanism of miRNA-145 in ovarian cancer through meta-analysis and bioinformatics analysis.

This article is from PLoS Computational Biology , volume 10 . Abstract The interdisciplinary nature of bioinformatics makes it an ideal framework to develop activities enabling enquiry-based learning. We describe here the development and implementation of a pilot project to use bioinformatics-based research activities in high schools, called “Bioinformatics@school.” It includes web-based research projects that students can pursue alone or under teacher supervision and a teacher training program. The project is organized so as to enable discussion of key results between students and teachers. After successful trials in two high schools, as measured by questionnaires, interviews, and assessment of knowledge acquisition, the project is expanding by the action of the teachers involved, who are helping us develop more content and are recruiting more teachers and schools.

Talk by Professor Victoria Stodden, Department of Statistics, Columbia University. The talk was given at UC Berkeley. Abstract Large-scale sequencing projects paved the way for the adoption of pioneering open data policies, making bioinformatics one the leading fields for data availability and access. In this talk I will trace the history of open data in -omics based research, and discuss how open code as well are data are being addressed today. This will include discussing leading edge tools and computational infrastructure developments intended to facilitate reproducible research through workflow tracking, computational environments, and data and code sharing.

In-stent restenosis (ISR) is one of the most important complications and impacts the long-term effects after percutaneous coronary intervention (PCI) in patients with coronary heart disease (CHD). Related studies have revealed that microRNA (miRNA) can predict ISR in CHD patients. MiRNA-126 may be a potential biomarker for the diagnosis of ISR. However, the accuracy of miRNA-126 in the diagnosis of ISR is still controversial. Therefore, this study carried out meta-analysis to further evaluate the accuracy of miRNA-126 in the diagnosis of ISR. At the same time, bioinformatics is used to predict the target genes and miRNA-126 may be involved in regulation, so as to provide theoretical support for the precise treatment of CHD.

Protocol for a scoping review and usability evaluation of Workflow Management Systems (WMS) for bioinformatics. This is the first version of the protocol.

This article is from Viruses , volume 2 . Abstract The drastic increase in the number of coronaviruses discovered and coronavirus genomes being sequenced have given us an unprecedented opportunity to perform genomics and bioinformatics analysis on this family of viruses. Coronaviruses possess the largest genomes (26.4 to 31.7 kb) among all known RNA viruses, with G + C contents varying from 32% to 43%. Variable numbers of small ORFs are present between the various conserved genes (ORF1ab, spike, envelope, membrane and nucleocapsid) and downstream to nucleocapsid gene in different coronavirus lineages. Phylogenetically, three genera, Alphacoronavirus, Betacoronavirus and Gammacoronavirus, with Betacoronavirus consisting of subgroups A, B, C and D, exist. A fourth genus, Deltacoronavirus, which includes bulbul coronavirus HKU11, thrush coronavirus HKU12 and munia coronavirus HKU13, is emerging. Molecular clock analysis using various gene loci revealed that the time of most recent common ancestor of human/civet SARS related coronavirus to be 1999–2002, with estimated substitution rate of 4×10−4 to 2×10−2 substitutions per site per year. Recombination in coronaviruses was most notable between different strains of murine hepatitis virus (MHV), between different strains of infectious bronchitis virus, between MHV and bovine coronavirus, between feline coronavirus (FCoV) type I and canine coronavirus generating FCoV type II, and between the three genotypes of human coronavirus HKU1 (HCoV-HKU1). Codon usage bias in coronaviruses were observed, with HCoV-HKU1 showing the most extreme bias, and cytosine deamination and selection of CpG suppressed clones are the two major independent biological forces that shape such codon usage bias in coronaviruses.

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This Center is made up of an integrated set of research projects in five areas. The overall mission of the center is to utilize state-of-the-art systems biology approaches to the generation of novel therapies and diagnostics for human diseases. Drug Discovery & Delivery: Biologically relevant compounds that can be linked to effects on specific gene expression patterns, creating new drug targets. Included in this program are two new start-up companies. Cancer: Identify targets to inhibit tumor growth and cell proliferation. Neurodegenerative Disease: Investigating the disease mechanisms of several neurological disorders, including Alzheimer's, MS, Krabbe's and Parkinson's disease. Major themes include demyelination, amyloid plaque formation, and loss of cellular function. Cardio-Vascular disease; Mechanisms by which inflammatory processes associated with clinical aspiration events progress to pneumonitis and ventilator-associated pneumonias; sudden cardiac failure due to arrhythmias. Pathogenesis & Biodefense: Investigation of virulence factors for bacteria and viruses important in human disease and in bio-warfare. Novel vaccines and anti-microbial agents will be developed based on structure-function understanding of these factors. Data Intensive Core; Analysis of genomic, proteomic, epidemiological and clinical data, imaging, and modeling.

Indexing massive data sets is extremely expensive for large scale problems. In many fields, huge amounts of data are currently generated, however extracting meaningful information from voluminous data sets, such as computing similarity between elements, is far from being trivial. It remains nonetheless a fundamental need. This work proposes a probabilistic data structure based on a minimal perfect hash function for indexing large sets of keys. Our structure out-compete the hash table for construction, query times and for memory usage, in the case of the indexation of a static set. To illustrate the impact of algorithms performances, we provide two applications based on similarity computation between collections of sequences, and for which this calculation is an expensive but required operation. In particular, we show a practical case in which other bioinformatics tools fail to scale up the tested data set or provide lower recall quality results.

Indexing massive data sets is extremely expensive for large scale problems. In many fields, huge amounts of data are currently generated, however extracting meaningful information from voluminous data sets, such as computing similarity between elements, is far from being trivial. It remains nonetheless a fundamental need. This work proposes a probabilistic data structure based on a minimal perfect hash function for indexing large sets of keys. Our structure out-compete the hash table for construction, query times and for memory usage, in the case of the indexation of a static set. To illustrate the impact of algorithms performances, we provide two applications based on similarity computation between collections of sequences, and for which this calculation is an expensive but required operation. In particular, we show a practical case in which other bioinformatics tools fail to scale up the tested data set or provide lower recall quality results.

Harriet Dashnow https://linux.conf.au/schedule/30302/view_talk What is a bioinformatician, and how do I become one? Many bioinformaticians start out in other fields, like biology, computer science or statistics, then transition to bioinformatics later in their careers. In my search to help ease the transition for biologists moving into the era of big data biology, I have become involved in the Software Carpentry and Data Carpentry training organisations. These workshops have proven to be an amazing tool for helping biologists learn computational skills. I will share the lessons I have learned running these workshops, and start a discussion about how we can provide biology training for those with computational and analytic skills wishing to make the transition into bioinformatics.

The Microsoft Biology Initiative (MBI) is an effort in Microsoft Research to bring new technology and tools to the area of bioinformatics and biology. This initiative is comprised of two primary components, the Microsoft Biology Foundation (MBF) and the Microsoft Biology Tools (MBT). The Microsoft Biology Foundation (MBF) is a language-neutral bioinformatics toolkit built as an extension to the Microsoft .NET Framework, initially aimed at the area of Genomics research. Currently, it implements a range of parsers for common bioinformatics file formats; a range of algorithms for manipulating DNA, RNA, and protein sequences; and a set of connectors to biological web services such as NCBI BLAST. MBF is available under an open source license, and executables, source code, demo applications, and documentation are freely downloadable. The Microsoft Biology Tools (MBT) are a collection of tools targeted at helping the biology and bioinformatics researcher be more productive in making scientific discoveries. The tools provided here take advantage of the capabilities provided in the Microsoft Biology Foundation, and are good examples of how MBF can be used to create other tools. This tutorial will provide an overview of the library, details about how to extend and re-use the library, and demonstrations of the tools released that use the library: The MSR Biology Extension for Excel and the MSR Sequence Assembler. ©2010 Microsoft Corporation. All rights reserved.

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BIOINFORMATICS ADVANCES IN GENOMICS – A REVIEW

BIOINFORMATICS ADVANCES IN GENOMICS – A REVIEW

As the most common type of cerebrovascular disease, ischemic stroke is the disturbance of cerebrovascular circulation caused by various factors, with complex pathogenesis. At present, the molecular mechanism of ischemic stroke is still unclear, and there lacks early diagnostic markers. Therefore, there is an urgent need to find effective preventive measures, active diagnostic methods and rapid treatment measures. In recent years, related studies have displayed that Long non-coding RNAs (lncRNAs) is related to the prognosis of ischemic stroke. However, the results are not supported by some evidence. Therefore, in this study, meta-analysis was used to analyze the relationship between lncRNAs and the prognosis of ischemic stroke. In addition, we carried out bioinformatics analysis to study the action mechanism and related pathways of lncRNAs in ischemic stroke.

Bioinformatics is an interdisciplinary field of biomedical engineering and biotechnology that incorporates computational, mathematical, statistical analysis and information technology to provide a better solution to biological and biomedical engineering problems. Bioinformatics aims at the advancement of biomedical engineering by furnishing an open platform for biomedical engineers, researchers, educators, and scientists.Biomedical engineering and bioinformatics is experiencing remarkable expansion and recognition at present. Applied bioinformatics is thus right now is a hot, alluring and captivating field that incorporates life sciences, biomedical sciences, computationl biology and software engineering for better future of mankind.

General Biology Laboratory

General Biology Laboratory

Preeclampsia has genetic correlation. Many studies have shown that microRNA (miRNA) polymorphism is highly associated with preeclampsia, but the results are inconsistent. The purpose of this study is to systematically evaluate the relationship between miRNA polymorphism and preeclampsia.

Preeclampsia has genetic correlation. Many studies have shown that microRNA (miRNA) polymorphism is highly associated with preeclampsia, but the results are inconsistent. The purpose of this study is to systematically evaluate the relationship between miRNA polymorphism and preeclampsia.

Preeclampsia has genetic correlation. Many studies have shown that microRNA (miRNA) polymorphism is highly associated with preeclampsia, but the results are inconsistent. The purpose of this study is to systematically evaluate the relationship between miRNA polymorphism and preeclampsia.

In response to the potential use of viruses as biological weapons, we have established the Viral Biological-threat Bioinformatics Resource (VBBR) that collects, catalogs, annotates, and analyzes genetic information related to potential viral threats. This work expands upon available knowledge of virus replication, pathogenicity, and virus-host interactions on the basis of individual protein domains, individual genes, and whole genomes. To date, we have constructed a genome and gene sequence database that has been populated with the sequence information for viruses currently listed on the NIH and CDC priority pathogen list. We have also developed a variety of analytical and visualization tools that aid in the analysis of the genomic information coded for by these viruses. Finally, the information developed as a result of this work has been made available to the scientific community through a (currently access-controlled) web site (http://vbbr.genome.uab.edu) that supports research efforts to develop environmental detectors, diagnostics, antiviral compounds, new vaccines, and animal models in support of biodefense research goals.

In response to the potential use of viruses as biological weapons, we have established the Viral Biological-threat Bioinformatics Resource (VBBR) that collects, catalogs, annotates, and analyzes genetic information related to potential viral threats. This work expands upon available knowledge of virus replication, pathogenicity, and virus-host interactions on the basis of individual protein domains, individual genes, and whole genomes. To date, we have constructed a genome and gene sequence database that has been populated with the sequence information for viruses currently listed on the NIH and CDC priority pathogen list. We have also developed a variety of analytical and visualization tools that aid in the analysis of the genomic information coded for by these viruses. Finally, the information developed as a result of this work has been made available to the scientific community through a (currently access-controlled) web site (http://vbbr.genome.uab.edu) that supports research efforts to develop environmental detectors, diagnostics, antiviral compounds, new vaccines, and animal models in support of biodefense research goals.