Microbiome Datasets

Microbiome datasets are collections of genomic and metagenomic data characterizing microbial communities, primarily aiming to understand their composition, function, and relationship with host health or environmental factors. Current research heavily utilizes machine learning, employing graph neural networks, diffusion models, and other advanced architectures like autoencoders and generative models to address challenges like data sparsity, high dimensionality, and class imbalance, often incorporating phylogenetic information. These analyses facilitate improved disease prediction, personalized medicine approaches, and a deeper understanding of microbial interactions and their functional roles in various ecosystems, ultimately advancing fields like precision medicine and sustainable agriculture.

Papers

October 18, 2024

Interpreting Microbiome Relative Abundance Data Using Symbolic Regression
Swagatam Haldar, Christoph Stein-Thoeringer, Vadim Borisov
Inherent Interpretability Novel Regression Model Interpretability Symbolic Expression Microbiome Datasets Microbiome Research Biological Insight Abundance Estimation

September 15, 2024

Recent advances in deep learning and language models for studying the microbiome
Binghao Yan, Yunbi Nam, Lingyao Li, Rebecca A. Deek, Hongzhe Li, Siyuan Ma
Language Model Deep Learning Recent Advance Microbiome Datasets Microbiome Research

August 10, 2024

Pretrained-Guided Conditional Diffusion Models for Microbiome Data Analysis
Xinyuan Shi, Fangfang Zhu, Wenwen Min
Conditional Diffusion Model Data Imputation Microbiome Datasets Microbiome Research

July 31, 2024

UMMAN: Unsupervised Multi-graph Merge Adversarial Network for Disease Prediction Based on Intestinal Flora
Dingkun Liu, Hongjie Zhou, Yilu Qu, Huimei Zhang, Yongdong Xu
Disease Prediction Microbiome Datasets Microbiome Research Adversarial Network

July 4, 2024

gFlora: a topology-aware method to discover functional co-response groups in soil microbial communities
Nan Chen, Merlijn Schram, Doina Bucur
Co Occurrence Microbiome Datasets Microbial Community Soil Temperature Ecological Network

June 28, 2024

Graph Neural Networks for Gut Microbiome Metaomic data: A preliminary work
Christopher Irwin, Flavio Mignone, Stefania Montani, Luigi Portinale
Graph Neural Network Microbiome Datasets Microbiome Research Encoder Feature Phylogenetic Network

June 7, 2024

Generative modeling of density regression through tree flows
Zhuoqun Wang, Naoki Awaya, Li Ma
Generative Modeling Conditional Density Microbiome Datasets Density Regression

April 29, 2024

Bayesian-Guided Generation of Synthetic Microbiomes with Minimized Pathogenicity
Nisha Pillai, Bindu Nanduri, Michael J Rothrock, Zhiqian Chen, Mahalingam Ramkumar
Microbiome Datasets Synthetic Microbiome

March 7, 2024

Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization
Dawid Płudowski, Antoni Zajko, Anna Kozak, Katarzyna Woźnica
Hyperparameter Optimization Tabular Datasets Warm Start Microbiome Datasets Heterogeneous Tabular Data

February 27, 2024

November 21, 2023

From Microbes to Methane: AI-Based Predictive Modeling of Feed Additive Efficacy in Dairy Cows
Yaniv Altshuler, Tzruya Calvao Chebach, Shalom Cohen
Microbiome Datasets Microbial Community Feed Additive Strawberry Tabletop Yield Forecasting Methane Flux

September 26, 2023

Cross-Validation for Training and Testing Co-occurrence Network Inference Algorithms
Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, Toby Dylan Hocking
Training Data Cross Validation Network Inference Microbiome Datasets Microbial Community

June 30, 2023

Application of data engineering approaches to address challenges in microbiome data for optimal medical decision-making
Isha Thombre, Pavan Kumar Perepu, Shyam Kumar Sudhakar
Application Proficiency Technical Challenge Random Forest Microbiome Datasets Microbiome Research

June 19, 2023

Human Limits in Machine Learning: Prediction of Plant Phenotypes Using Soil Microbiome Data
Rosa Aghdam, Xudong Tang, Shan Shan, Richard Lankau, Claudia Solís-Lemus
Machine Learning Human Prediction Microbiome Datasets Microbiome Research Soil Temperature Plant Phenotype Human Capability

May 20, 2022

Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome
Elliott Gordon-Rodriguez, Thomas P. Quinn, John P. Cunningham
Data Augmentation Predictive Model Compositional Data Microbiome Datasets Microbiome Research

May 15, 2022

Supervised Learning and Model Analysis with Compositional Data
Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister
Supervised Learning Model Evaluation Kernel Based Compositional Data Microbiome Datasets Microbiome Research

March 2, 2022

Understanding microbiome dynamics via interpretable graph representation learning
Kateryna Melnyk, Kuba Weimann, Tim O. F. Conrad
interactiOn Pattern Evolving Graph Microbiome Datasets Interpretable Graph Microbiome Research

November 28, 2021

Dimensionality Reduction of Longitudinal 'Omics Data using Modern Tensor Factorization
Uria Mor, Yotam Cohen, Rafael Valdes-Mas, Denise Kviatcovsky, Eran Elinav, Haim Avron
Dimensionality Reduction Tensor Factorization Longitudinal Data Microbiome Datasets

November 9, 2021

Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis
Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran
Contextual Representation Microbiome Datasets

Microbiome Datasets

Papers

Interpreting Microbiome Relative Abundance Data Using Symbolic Regression

Recent advances in deep learning and language models for studying the microbiome

Pretrained-Guided Conditional Diffusion Models for Microbiome Data Analysis

UMMAN: Unsupervised Multi-graph Merge Adversarial Network for Disease Prediction Based on Intestinal Flora

gFlora: a topology-aware method to discover functional co-response groups in soil microbial communities

Graph Neural Networks for Gut Microbiome Metaomic data: A preliminary work

Generative modeling of density regression through tree flows

Bayesian-Guided Generation of Synthetic Microbiomes with Minimized Pathogenicity

Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization

Supervised machine learning for microbiomics: bridging the gap between current and best practices

Few-shot adaptation for morphology-independent cell instance segmentation

From Microbes to Methane: AI-Based Predictive Modeling of Feed Additive Efficacy in Dairy Cows

Cross-Validation for Training and Testing Co-occurrence Network Inference Algorithms

Application of data engineering approaches to address challenges in microbiome data for optimal medical decision-making

Human Limits in Machine Learning: Prediction of Plant Phenotypes Using Soil Microbiome Data

Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome

Supervised Learning and Model Analysis with Compositional Data

Understanding microbiome dynamics via interpretable graph representation learning

Dimensionality Reduction of Longitudinal 'Omics Data using Modern Tensor Factorization

Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis