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PASTMUS: mapping functional elements at single amino acid resolution in human cells

Genome Biology - BiomedCentral - Mon, 16/12/2019 - 5:30am
Identification of functional elements for a protein of interest is important for achieving a mechanistic understanding. However, it remains cumbersome to assess each and every amino acid of a given protein in ...
Categories: Bioinformatics Trends

SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies

Genome Biology - BiomedCentral - Mon, 16/12/2019 - 5:30am
Genomic differences range from single nucleotide differences to complex structural variations. Current methods typically annotate sequence differences ranging from SNPs to large indels accurately but do not un...
Categories: Bioinformatics Trends

Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline

Genome Biology - BiomedCentral - Mon, 16/12/2019 - 5:30am
Sequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and...
Categories: Bioinformatics Trends

deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index

Genome Biology - BiomedCentral - Mon, 16/12/2019 - 5:30am
The alignment of long-read RNA sequencing reads is non-trivial due to high sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass alignment approach, which constructs graph-b...
Categories: Bioinformatics Trends

EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data

BMC Bioinformatics - Mon, 16/12/2019 - 5:30am
High throughput sequence data has provided in depth means of molecular characterization of populations. When recorded at numerous time steps, such data can reveal the evolutionary dynamics of the population un...
Categories: Bioinformatics Trends

Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data

BMC Bioinformatics - Mon, 16/12/2019 - 5:30am
Late-Onset Alzheimer’s Disease (LOAD) is a leading form of dementia. There is no effective cure for LOAD, leaving the treatment efforts to depend on preventive cognitive therapies, which stand to benefit from ...
Categories: Bioinformatics Trends

Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning

BMC Bioinformatics - Mon, 16/12/2019 - 5:30am
Development of new drugs is a time-consuming and costly process, and the cost is still increasing in recent years. However, the number of drugs approved by FDA every year per dollar spent on development is dec...
Categories: Bioinformatics Trends

HOPS: automated detection and authentication of pathogen DNA in archaeological remains

Genome Biology - Mon, 16/12/2019 - 5:30am
High-throughput DNA sequencing enables large-scale metagenomic analyses of complex biological systems. Such analyses are not restricted to present-day samples and can also be applied to molecular data from arc...
Categories: Bioinformatics Trends

PASTMUS: mapping functional elements at single amino acid resolution in human cells

Genome Biology - Mon, 16/12/2019 - 5:30am
Identification of functional elements for a protein of interest is important for achieving a mechanistic understanding. However, it remains cumbersome to assess each and every amino acid of a given protein in ...
Categories: Bioinformatics Trends

SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies

Genome Biology - Mon, 16/12/2019 - 5:30am
Genomic differences range from single nucleotide differences to complex structural variations. Current methods typically annotate sequence differences ranging from SNPs to large indels accurately but do not un...
Categories: Bioinformatics Trends

Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline

Genome Biology - Mon, 16/12/2019 - 5:30am
Sequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and...
Categories: Bioinformatics Trends

deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index

Genome Biology - Mon, 16/12/2019 - 5:30am
The alignment of long-read RNA sequencing reads is non-trivial due to high sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass alignment approach, which constructs graph-b...
Categories: Bioinformatics Trends

ngsReports: A Bioconductor package for managing FastQC reports and other NGS related log files

Bioinformatics Oxford Journals - Mon, 16/12/2019 - 5:30am
AbstractMotivationHigh throughput next generation sequencing (NGS) has become exceedingly cheap, facilitating studies to be undertaken containing large sample numbers. Quality control (QC) is an essential stage during analytic pipelines and the outputs of popular bioinformatics tools such as FastQC and Picard can provide information on individual samples. Although these tools provide considerable power when carrying out QC, large sample numbers can make inspection of all samples and identification of systemic bias a challenge.ResultsWe present ngsReports, an R package designed for the management and visualisation of NGS reports from within an R environment. The available methods allow direct import into R of FastQC reports along with outputs from other tools. Visualisation can be carried out across many samples using default, highly-customisable plots with options to perform hierarchical clustering to quickly identify outlier libraries. Moreover, these can be displayed in an interactive shiny app or HTML report for ease of analysis.AvailabilityThe ngsReports package is available on Bioconductor and the GUI shiny app is available at https://github.com/UofABioinformaticsHub/shinyNgsreports
Categories: Bioinformatics Trends

GlyMDB: Glycan Microarray Database and Analysis Toolset

Bioinformatics Oxford Journals - Mon, 16/12/2019 - 5:30am
AbstractMotivationGlycan microarrays are capable of illuminating the interactions of glycan-binding proteins (GBPs) against hundreds of defined glycan structures, and have revolutionized the investigations of protein-carbohydrate interactions underlying numerous critical biological activities. However, it is difficult to interpret microarray data and identify structural determinants promoting glycan binding to GBPs due to the ambiguity in microarray fluorescence intensity and complexity in branched glycan structures. To facilitate analysis of glycan microarray data alongside protein structure, we have built the glycan microarray database (GlyMDB), a web-based resource including a searchable database of glycan microarray samples and a toolset for data/structure analysis.ResultsThe current GlyMDB provides data visualization and glycan-binding motif discovery for 5,203 glycan microarray samples collected from the Consortium for Functional Glycomics. The unique feature of GlyMDB is to link microarray data to PDB structures. The GlyMDB provides different options for database query, and allows users to upload their microarray data for analysis. After search or upload is complete, users can choose the criterion for binder vs. non-binder classification. They can view the signal intensity graph including the binder/non-binder threshold followed by a list of glycan binding motifs. One can also compare the fluorescence intensity data from two different microarray samples. A protein sequence-based search is performed using BLAST to match microarray data with all available PDB structures containing glycans. The glycan ligand information is displayed, and links are provided for structural visualization and redirection to other modules in GlycanStructure.ORG for further investigation of glycan binding sites and glycan structures.Availability and implementationhttp://www.glycanstructure.org/glymdb.Supplementary informationSupplementary dataSupplementary data are available at Bioinformatics online.
Categories: Bioinformatics Trends

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April 2020