review article | Q7318358 |
scholarly article | Q13442814 |
P2093 | author name string | Baiba Vilne | |
Irēna Meistere | |||
Lelde Grantiņa-Ieviņa | |||
Juris Ķibilds | |||
P2860 | cites work | The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes | Q21284200 |
BLAST+: architecture and applications | Q21284368 | ||
Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella | Q24286921 | ||
Metagenomic microbial community profiling using unique clade-specific marker genes | Q24599864 | ||
Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak. | Q51783026 | ||
chewBBACA: A complete suite for gene-by-gene schema creation and strain identification. | Q51783712 | ||
Opportunities and obstacles for deep learning in biology and medicine. | Q52331906 | ||
A genomic overview of the population structure of Salmonella. | Q55036075 | ||
Tracking antibiotic resistance gene pollution from different sources using machine-learning classification. | Q55353550 | ||
A pan-genome-based machine learning approach for predicting antimicrobial resistance activities of the Escherichia coli strains. | Q55492324 | ||
Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica. | Q55523797 | ||
SKESA: strategic k-mer extension for scrupulous assemblies | Q57026999 | ||
Using machine learning to predict antimicrobial minimum inhibitory concentrations and associated genomic features for nontyphoidal | Q58545265 | ||
Zoonotic Source Attribution of Salmonella enterica Serotype Typhimurium Using Genomic Surveillance Data, United States | Q60922595 | ||
Using average nucleotide identity to improve taxonomic assignments in prokaryotic genomes at the NCBI | Q63256992 | ||
Characterization of Emetic and Diarrheal Strains From a 2016 Foodborne Outbreak Using Whole-Genome Sequencing: Addressing the Microbiological, Epidemiological, and Bioinformatic Challenges | Q64251941 | ||
Mechanistic models versus machine learning, a fight worth fighting for the biological community? | Q88698220 | ||
Use of Whole-Genome Sequencing for Food Safety and Public Health in the United States | Q92717431 | ||
CFSAN SNP Pipeline: an automated method for constructing SNP matrices from next-generation sequence data | Q110949957 | ||
Ray: simultaneous assembly of reads from a mix of high-throughput sequencing technologies | Q24609520 | ||
QIIME allows analysis of high-throughput community sequencing data | Q24616873 | ||
SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing | Q24629733 | ||
ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences | Q24634141 | ||
Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities | Q24647611 | ||
Velvet: algorithms for de novo short read assembly using de Bruijn graphs | Q24657623 | ||
RNAmmer: consistent and rapid annotation of ribosomal RNA genes | Q24675768 | ||
Mash: fast genome and metagenome distance estimation using MinHash | Q24707164 | ||
The neighbor-joining method: a new method for reconstructing phylogenetic trees | Q25939010 | ||
BEAST: Bayesian evolutionary analysis by sampling trees | Q27860723 | ||
Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations | Q28068009 | ||
Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics | Q28075867 | ||
Microbial bioinformatics for food safety and production | Q28081332 | ||
CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database | Q28584458 | ||
SPANDx: a genomics pipeline for comparative analysis of large haploid whole genome re-sequencing datasets | Q28655611 | ||
Fast filtering for RNA homology search | Q28743147 | ||
SignalP 4.0: discriminating signal peptides from transmembrane regions | Q29547202 | ||
RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees | Q29547265 | ||
Prodigal: prokaryotic gene recognition and translation initiation site identification | Q29547611 | ||
FastTree: computing large minimum evolution trees with profiles instead of a distance matrix | Q29614577 | ||
BLAST: at the core of a powerful and diverse set of sequence analysis tools | Q29615883 | ||
Prokka: rapid prokaryotic genome annotation | Q29616643 | ||
PathogenFinder--distinguishing friend from foe using bacterial whole genome sequence data | Q30690828 | ||
PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data | Q30833683 | ||
Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data | Q30948004 | ||
Reconstructing 16S rRNA genes in metagenomic data | Q30971304 | ||
VFDB 2016: hierarchical and refined dataset for big data analysis--10 years on | Q31025236 | ||
Gene prediction in metagenomic fragments based on the SVM algorithm. | Q31118752 | ||
A modification of the PHYLIP program: A solution for the redundant cluster problem, and an implementation of an automatic bootstrapping on trees inferred from original data | Q31165360 | ||
VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens | Q33316857 | ||
TACOA: taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach | Q33408370 | ||
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction | Q33524574 | ||
Comprehensive bioinformatics analysis of Mycoplasma pneumoniae genomes to investigate underlying population structure and type-specific determinants | Q33565500 | ||
Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation | Q33622593 | ||
Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions | Q33693333 | ||
StrainSeeker: fast identification of bacterial strains from raw sequencing reads using user-provided guide trees | Q33709329 | ||
PanWeb: A web interface for pan-genomic analysis | Q33725008 | ||
Kraken: ultrafast metagenomic sequence classification using exact alignments | Q33742022 | ||
BIGSdb: Scalable analysis of bacterial genome variation at the population level. | Q33767145 | ||
PulseNet International: Vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance | Q33822884 | ||
Bayesian semi-supervised classification of bacterial samples using MLST databases | Q33972144 | ||
IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth | Q34229322 | ||
Reduced set of virulence genes allows high accuracy prediction of bacterial pathogenicity in humans | Q34390820 | ||
Accurate phylogenetic classification of variable-length DNA fragments | Q34593023 | ||
The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes | Q34676711 | ||
MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes | Q34862099 | ||
Reconstructing each cell's genome within complex microbial communities-dream or reality? | Q34869203 | ||
MGC: a metagenomic gene caller | Q34882436 | ||
Solving the problem of comparing whole bacterial genomes across different sequencing platforms | Q35222674 | ||
MetaVelvet-SL: an extension of the Velvet assembler to a de novo metagenomic assembler utilizing supervised learning | Q35233831 | ||
Update on RefSeq microbial genomes resources | Q35253461 | ||
PERGA: a paired-end read guided de novo assembler for extending contigs using SVM and look ahead approach | Q35476199 | ||
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets | Q35554085 | ||
MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach | Q36317841 | ||
A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy. | Q36367250 | ||
Next-Generation Sequencing and Comparative Analysis of Sequential Outbreaks Caused by Multidrug-Resistant Acinetobacter baumannii at a Large Academic Burn Center | Q36644684 | ||
Antimicrobial Resistance Prediction in PATRIC and RAST. | Q37000598 | ||
ANItools web: a web tool for fast genome comparison within multiple bacterial strains | Q37015389 | ||
Rapid whole-genome sequencing for detection and characterization of microorganisms directly from clinical samples | Q37546541 | ||
Multilocus Sequence Typing for Interpreting Blood Isolates of Staphylococcus epidermidis | Q37644882 | ||
The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). | Q37661996 | ||
A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens | Q37694453 | ||
Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli | Q37713782 | ||
Explaining microbial phenotypes on a genomic scale: GWAS for microbes | Q38102667 | ||
Omics approaches in food safety: fulfilling the promise? | Q38191377 | ||
PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes | Q38342057 | ||
A supervised statistical learning approach for accurate Legionella pneumophila source attribution during outbreaks. | Q38618052 | ||
Whole-Genome Sequencing of Bacterial Pathogens: the Future of Nosocomial Outbreak Analysis | Q38635425 | ||
MetaGene: prokaryotic gene finding from environmental genome shotgun sequences | Q39118049 | ||
Classification of Listeria monocytogenes persistence in retail delicatessen environments using expert elicitation and machine learning. | Q39182193 | ||
The evolution of One Health: a decade of progress and challenges for the future | Q39263984 | ||
Advances in Rapid Identification and Susceptibility Testing of Bacteria in the Clinical Microbiology Laboratory: Implications for Patient Care and Antimicrobial Stewardship Programs | Q39274504 | ||
Roary: rapid large-scale prokaryote pan genome analysis | Q39769468 | ||
Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences | Q39788453 | ||
JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. | Q40312977 | ||
Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences. | Q41088773 | ||
Hierarchical and spatially explicit clustering of DNA sequences with BAPS software | Q41436456 | ||
Metagenome fragment classification using N-mer frequency profiles | Q41947344 | ||
Identification of acquired antimicrobial resistance genes | Q41981445 | ||
Orphelia: predicting genes in metagenomic sequencing reads | Q42021729 | ||
SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology | Q42277652 | ||
Whole genome sequencing (WGS) for food-borne pathogen surveillance and control - taking the pulse. | Q42335711 | ||
Updating benchtop sequencing performance comparison | Q43497116 | ||
OrthoANI: An improved algorithm and software for calculating average nucleotide identity | Q45340509 | ||
Patchy promiscuity: machine learning applied to predict the host specificity of Salmonella enterica and Escherichia coli. | Q45800600 | ||
PATRIC as a unique resource for studying antimicrobial resistance. | Q45945275 | ||
High Throughput Sequencing for Detection of Foodborne Pathogens. | Q46090917 | ||
Gene Prediction in Metagenomic Fragments with Deep Learning | Q46237755 | ||
Surveillance of Foodborne Pathogens: Towards Diagnostic Metagenomics of Fecal Samples. | Q47210600 | ||
Efficiency of PacBio long read correction by 2nd generation Illumina sequencing. | Q47264805 | ||
DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data | Q47692122 | ||
kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome | Q47936283 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P921 | main subject | machine learning | Q2539 |
P304 | page(s) | 1722 | |
P577 | publication date | 2019-08-06 | |
P1433 | published in | Frontiers in Microbiology | Q27723481 |
P1476 | title | Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease Outbreaks | |
P478 | volume | 10 |