Project description:Somatic coliphages are alternative indicators of fecal pollution and attractive surrogates for viral pathogens. Here, we report the draft genome sequences of three replicate plaques from a novel Myoviridae bacteriophage isolated from raw wastewater. These genomes were similar to felix01virus phage and are predicted to contain up to 148 protein-coding genes.

| S-EPMC6597681 | biostudies-literature

baseLess: lightweight detection of sequences in raw MinION data.

Project description:SummaryWith its candybar form factor and low initial investment cost, the MinION brought affordable portable nucleic acid analysis within reach. However, translating the electrical signal it outputs into a sequence of bases still requires mid-tier computer hardware, which remains a caveat when aiming for deployment of many devices at once or usage in remote areas. For applications focusing on detection of a target sequence, such as infectious disease monitoring or species identification, the computational cost of analysis may be reduced by directly detecting the target sequence in the electrical signal instead. Here, we present baseLess, a computational tool that enables such target-detection-only analysis. BaseLess makes use of an array of small neural networks, each of which efficiently detects a fixed-size subsequence of the target sequence directly from the electrical signal. We show that baseLess can accurately determine the identity of reads between three closely related fish species and can classify sequences in mixtures of 20 bacterial species, on an inexpensive single-board computer.Availability and implementationbaseLess and all code used in data preparation and validation are available on Github at https://github.com/cvdelannoy/baseLess, under an MIT license. Used validation data and scripts can be found at https://doi.org/10.4121/20261392, under an MIT license.Supplementary informationSupplementary data are available at Bioinformatics Advances online.

| S-EPMC9936955 | biostudies-literature

A dataset of labelled objects on raw video sequences.

Project description:We present an object labelled dataset called SFU-HW-Objects-v1, which contains object labels for a set of raw video sequences. The dataset can be useful for the cases where both object detection accuracy and video coding efficiency need to be evaluated on the same dataset. Object ground-truths for 18 of the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences have been labelled. The object categories used for the labeling are based on the Common Objects in Context (COCO) labels. A total of 21 object classes are found in test sequences, out of the 80 original COCO label classes. Brief descriptions of the labeling process and the structure of the dataset are presented.

| S-EPMC7797526 | biostudies-literature

Genetic Structure of Duplicated Sequences Revealed by Genotyping Single Sperm

Project description:Three different experimental approaches were evaluated for discrimination of genomic variance in and between duplicated sequences using 48 markers in duplicon regions and 17 SNPs in unique sequences previously characterized in another study. We found only the method high-throughput single sperm typing could conclusively resolve the alleles of all markers. Resulting data from single sperm analysis were also used to examine the genetic structure of duplicon markers in the human population. Single sperm typing can be a rapid, efficient and accurate method for initial screening and assessment of genetic variation and for detailed genetic analysis of duplicon markers. Keywords: Genotyping

2008-07-25 | GSE11957 | GEO

Project description:Development of genomic resources for Neo-Astragalus (Fabaceae)

| PRJNA755707 | ENA