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MicroPheno: Predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Alterations in the gut microbiome of children with severe ulcerative colitis

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Analysis of 16S rRNA Gene Amplicon Sequences Using the QIIME Software Package

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Host Phenotype Prediction from Differentially Abundant Microbes Using RoDEO

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Manipulating the soil microbiome to increase soil health and plant fertility

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Specificity in Chemical Profiles of Workers, Brood and Mutualistic Fungi in Atta, Acromyrmex, and Sericomyrmex Fungus-growing Ants

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MetaDP: a comprehensive web server for disease prediction of 16S rRNA metagenomic datasets

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The Prevalence and Geographic Distribution of Crohn’s Disease and Ulcerative Colitis in the United States

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Diet-Induced Obesity Is Linked to Marked but Reversible Alterations in the Mouse Distal Gut Microbiome

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The Treatment-Naive Microbiome in New-Onset Crohn’s Disease

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Cutaneous Leishmaniasis Induces a Transmissible Dysbiotic Skin Microbiota that Promotes Skin Inflammation

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Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification

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A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria

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Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

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Bacterial Community Structure in the Drinking Water Microbiome Is Governed by Filtration Processes

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Random Forests

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Least Squares Support Vector Machine Classifiers

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An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea

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Structure, function and diversity of the healthy human microbiome

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Fast and sensitive taxonomic classification for metagenomics with Kaiju

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QIIME allows analysis of high-throughput community sequencing data

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Taxonomic metagenome sequence assignment with structured output models

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Accurate phylogenetic classification of variable-length DNA fragments

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A perspective on 16S rRNA operational taxonomic unit clustering using sequence similarity

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The human microbiome: at the interface of health and disease

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Embracing the unknown: disentangling the complexities of the soil microbiome

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Meta-analysis of gut microbiome studies identifies disease-specific and shared responses

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Dysbiosis in chronic periodontitis: Key microbial players and interactions with the human host

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Gastrointestinal Microbiome Signatures of Pediatric Patients With Irritable Bowel Syndrome

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The Human Intestinal Microbiome in Health and Disease

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Forensic identification using skin bacterial communities

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Explaining microbial phenotypes on a genomic scale: GWAS for microbes

inferredcites →https://doi.org/10.1093/bib/bbw068openalex-snapshot

Deep learning in bioinformatics

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A fast, lock-free approach for efficient parallel counting of occurrences of k -mers

inferredcites →https://doi.org/10.1093/bioinformatics/btr381openalex-snapshot

UCHIME improves sensitivity and speed of chimera detection

inferredcites →https://doi.org/10.1093/bioinformatics/btv683openalex-snapshot

Large-scale machine learning for metagenomics sequence classification

inferredcites →https://doi.org/10.1093/nar/gks1219openalex-snapshot

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

inferredcites →https://doi.org/10.1093/nar/gkt241openalex-snapshot

Surprisingly extensive mixed phylogenetic and ecological signals among bacterial Operational Taxonomic Units

inferredcites →https://doi.org/10.1097/mcg.0000000000000046openalex-snapshot

Fecal Microbiota Transplantation for the Treatment of Clostridium difficile Infection

inferredcites →https://doi.org/10.1101/gr.085464.108openalex-snapshot

Microbial community profiling for human microbiome projects: Tools, techniques, and challenges

inferredcites →https://doi.org/10.1101/gr.096651.109openalex-snapshot

The NIH Human Microbiome Project

inferredcites →https://doi.org/10.1109/tnb.2015.2461219openalex-snapshot

Multi-Layer and Recursive Neural Networks for Metagenomic Classification

inferredcites →https://doi.org/10.1109/tpami.2013.50openalex-snapshot

Representation Learning: A Review and New Perspectives

inferredcites →https://doi.org/10.1111/j.1574-6976.2010.00251.xopenalex-snapshot

Supervised classification of human microbiota

inferredcites →https://doi.org/10.1126/science.1177486openalex-snapshot

Bacterial Community Variation in Human Body Habitats Across Space and Time

inferredcites →https://doi.org/10.1126/science.1241214openalex-snapshot

Gut Microbiota from Twins Discordant for Obesity Modulate Metabolism in Mice

inferredcites →https://doi.org/10.1126/science.1261359openalex-snapshot

Structure and function of the global ocean microbiome

inferredcites →https://doi.org/10.1126/science.aac8455openalex-snapshot

The global ocean microbiome

inferredcites →https://doi.org/10.1126/scitranslmed.aab2271openalex-snapshot

Early infancy microbial and metabolic alterations affect risk of childhood asthma

inferredcites →https://doi.org/10.1128/aem.01541-09openalex-snapshot

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

inferredcites →https://doi.org/10.1128/jcm.00162-17openalex-snapshot

Robust Microbiota-Based Diagnostics for Inflammatory Bowel Disease

inferredcites →https://doi.org/10.1128/jcm.01228-07openalex-snapshot

16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls

inferredcites →https://doi.org/10.1128/mbio.01012-14openalex-snapshot

Metatranscriptomics of the Human Oral Microbiome during Health and Disease

inferredcites →https://doi.org/10.1128/microbe.4.393.1openalex-snapshot

NIH Human Microbiome Project

inferredcites →https://doi.org/10.1136/gutjnl-2016-313235openalex-snapshot

A microbial signature for Crohn's disease

inferredcites →https://doi.org/10.1142/9789813235533_0018openalex-snapshot

Data-driven advice for applying machine learning to bioinformatics problems

inferredcites →https://doi.org/10.1186/1471-2164-14-641openalex-snapshot

Alignment-free supervised classification of metagenomes by recursive SVM

inferredcites →https://doi.org/10.1186/2049-2618-1-11openalex-snapshot

A comprehensive evaluation of multicategory classification methods for microbiomic data

inferredcites →https://doi.org/10.1186/gb-2014-15-3-r46openalex-snapshot

Kraken: ultrafast metagenomic sequence classification using exact alignments

inferredcites →https://doi.org/10.1186/s40168-015-0098-1openalex-snapshot

Erratum to: Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity

inferredcites →https://doi.org/10.1371/journal.pbio.1002020openalex-snapshot

Life in a World without Microbes

inferredcites →https://doi.org/10.1371/journal.pcbi.1004977openalex-snapshot

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights

inferredcites →https://doi.org/10.1371/journal.pcbi.1005518openalex-snapshot

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time

inferredcites →https://doi.org/10.1371/journal.pone.0073056openalex-snapshot

Metagenomic Predictions: From Microbiome to Complex Health and Environmental Phenotypes in Humans and Cattle

inferredcites →https://doi.org/10.1371/journal.pone.0087126openalex-snapshot

MetaMetaDB: A Database and Analytic System for Investigating Microbial Habitability

inferredcites →https://doi.org/10.1371/journal.pone.0121453openalex-snapshot

CoMeta: Classification of Metagenomes Using k-mers

inferredcites →https://doi.org/10.1371/journal.pone.0141287openalex-snapshot

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

inferredcites →https://doi.org/10.1371/journal.pone.0178338openalex-snapshot

Correction: Natalizumab stabilizes physical, cognitive, MRI, and OCT markers of disease activity: A prospective, non-randomized pilot study

inferredcites →https://doi.org/10.1378/chest.12-2854openalex-snapshot

The Airway Microbiome and Disease

inferredcites →https://doi.org/10.1681/asn.2013080905openalex-snapshot

The Gut Microbiome, Kidney Disease, and Targeted Interventions

inferredcites →https://doi.org/10.2307/1270093openalex-snapshot

Principal Component Analysis

inferredcites →https://doi.org/10.2307/2348864openalex-snapshot

Principal Component Analysis.

inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot

AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)

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Scikit-learn: Machine Learning in Python

inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.7717/peerj.545openalex-snapshot

Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.ymeth.2019.03.003openalex-snapshot

MetaPheno: A critical evaluation of deep learning and machine learning in metagenome-based disease prediction

inferred← citeshttps://doi.org/10.1038/s41598-022-04773-3openalex-snapshot

Multimodal deep learning applied to classify healthy and disease states of human microbiome

inferred← citeshttps://doi.org/10.1093/bioinformatics/bty954openalex-snapshot

DiTaxa: nucleotide-pair encoding of 16S rRNA for host phenotype and biomarker detection

inferred← citeshttps://doi.org/10.1101/419846openalex-snapshot

SpeciesMLP: Sequence based Multi-layer Perceptron for Amplicon Read Classification Using Real-time Data Augmentation

inferred← citeshttps://doi.org/10.1109/bibm.2018.8621287openalex-snapshot

AmpliconNet: Sequence Based Multi-layer Perceptron for Amplicon Read Classification Using Real-time Data Augmentation

inferred← citeshttps://doi.org/10.1109/cibec.2018.8641805openalex-snapshot

A Hybrid Machine Learning Approach for the Phenotypic Classification of Metagenomic Colon Cancer Reads Based on Kmer Frequency and Biomarker Profiling

inferred← citeshttps://doi.org/10.1371/journal.pcbi.1006721openalex-snapshot

16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses

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