GRAViTy-V2: a grounded viral taxonomy application DOI Creative Commons
Richard Mayne, Pakorn Aiewsakun, Dann Turner

и другие.

NAR Genomics and Bioinformatics, Год журнала: 2024, Номер 6(4)

Опубликована: Сен. 28, 2024

Abstract Taxonomic classification of viruses is essential for understanding their evolution. Genomic at higher taxonomic ranks, such as order or phylum, typically based on alignment and comparison amino acid sequence motifs in conserved genes. Classification lower genus species, usually nucleotide identities between genomic sequences. Building our whole-genome analytical framework, we here describe Genome Relationships Applied to Viral Taxonomy Version 2 (GRAViTy-V2), which encompasses a greatly expanded range features numerous optimisations, packaged an application that may be used general-purpose virus tool. Using 28 datasets derived from the ICTV 2022 taxonomy proposals, GRAViTy-V2 output was compared against human expert-curated classifications assignments 2023 round changes. produced taxonomies equivalent manually-curated versions down family level almost all cases, species levels. The majority discrepant results arose errors coding annotations INDSC records, inclusion incomplete genome sequences analysis. Analysis times ranged 1-506 min (median 3.59) with 17-1004 genomes mean length 3000–1 000 bases.

Язык: Английский

sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms DOI Creative Commons
Weiye Qian, Jiawei Sun, Tianyi Liu

и другие.

BMC Genomics, Год журнала: 2024, Номер 25(1)

Опубликована: Окт. 31, 2024

Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as new potential drug target the treatment of pathogen-induced disease. However, experimental methods for identifying sRNAs still require large investment human material resources.

Язык: Английский

Процитировано

1

Poplar: A Phylogenetics Pipeline DOI Creative Commons
Elizabeth Koning, Raga Krishnakumar

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 14, 2024

Abstract Motivation Generating phylogenetic trees from genomic data is essential in understanding biological systems. Each step of this complex process has received extensive attention the literature, and been significantly streamlined over years. Given volume publicly available genetic data, obtaining genomes for a wide selection known species straightforward. However, analyzing that same order to generate tree multi-step with legitimate scientific technical challenges, often requires significant input domain-area scientist. Results We present Poplar, new, computational pipeline, address logistical issues arise when constructing trees. It provides framework runs state-of-the-art software steps beginning genome or without an annotation, resulting tree. Running Poplar no external databases. In execution, it enables parallelism execution clusters cloud computing. The generated by match closely published usage performance far simpler quicker than manually running pipeline. Availability Implementation Freely on GitHub at https://github.com/sandialabs/poplar . Implemented using Python supported Linux. Supplementary Information Newick versions reference

Язык: Английский

Процитировано

1

Application of a metatranscriptomics technology, CSI-Dx, for the detection of pathogens associated with prosthetic joint infections DOI Creative Commons
Justin Wright, Jeremy R. Chen See,

Truc Ly

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Окт. 23, 2024

Preoperative identification of causal organism(s) is crucial for effective prosthetic joint infection treatment. Herein, we explore the clinical application a novel metatranscriptomic (MT) workflow, CSI-Dx, to detect pathogens associated with infection. MT provides insight into transcriptionally active microbes, overcoming limitations culture-based and available molecular methods. This study included 340 human synovial fluid specimens subjected CSI-Dx traditional Exploratory analyses were conducted determine sensitivity specificity detecting clinically-relevant taxa. Our findings provide insights microbial community composition from arthroplasty patients demonstrate potential utility aiding diagnosis. approach offers improved acceptable compared culture, enabling detection culturable non-culturable microorganisms. Furthermore, valuable information on antimicrobial resistance gene expression. While further optimization needed, integrating technologies like routine practice can revolutionize diagnosis by offering comprehensive snapshot pathogens.

Язык: Английский

Процитировано

0

Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network DOI
Yu He,

Zilan Ning,

Xinghui Zhu

и другие.

Interdisciplinary Sciences Computational Life Sciences, Год журнала: 2024, Номер unknown

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

0

GRAViTy-V2: a grounded viral taxonomy application DOI Creative Commons
Richard Mayne, Pakorn Aiewsakun, Dann Turner

и другие.

NAR Genomics and Bioinformatics, Год журнала: 2024, Номер 6(4)

Опубликована: Сен. 28, 2024

Abstract Taxonomic classification of viruses is essential for understanding their evolution. Genomic at higher taxonomic ranks, such as order or phylum, typically based on alignment and comparison amino acid sequence motifs in conserved genes. Classification lower genus species, usually nucleotide identities between genomic sequences. Building our whole-genome analytical framework, we here describe Genome Relationships Applied to Viral Taxonomy Version 2 (GRAViTy-V2), which encompasses a greatly expanded range features numerous optimisations, packaged an application that may be used general-purpose virus tool. Using 28 datasets derived from the ICTV 2022 taxonomy proposals, GRAViTy-V2 output was compared against human expert-curated classifications assignments 2023 round changes. produced taxonomies equivalent manually-curated versions down family level almost all cases, species levels. The majority discrepant results arose errors coding annotations INDSC records, inclusion incomplete genome sequences analysis. Analysis times ranged 1-506 min (median 3.59) with 17-1004 genomes mean length 3000–1 000 bases.

Язык: Английский

Процитировано

0