Tal Korem

Spatially Mapping the Mechanical and Structural Properties of the Seedling Uterine Fibroid-Myometrium Interface

This study maps the mechanical, structural, and compositional properties of seedling uterine fibroids at the fibroid-myometrium interface, revealing distinct differences compared to surrounding tissue.

End-to-end evaluation of pipelines for metagenome-assembled genomes reveals hidden performance gaps

The paper evaluates MAG pipelines using MAG-E, revealing performance gaps in assembly, binning, and quality control for the human gut microbiome.

A generalizable cross-continent prediction of esophageal squamous cell carcinoma using the oral microbiome

This study develops a machine learning model using oral microbiome data to predict esophageal squamous cell carcinoma, showing good performance across different geographic regions.

Comparative metagenomics using pan-metagenomics graphs

This paper introduces copangraph, a framework for comparative metagenomic analysis using sequence graphs, showing improved accuracy and computational efficiency in capturing genomic variation across microbial communities.

Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles

The paper identifies sample processing errors in microbiome studies using host genetic profiles from metagenomic sequencing and experimental metadata.

Compositional transformations can reasonably introduce phenotype-associated values into sparse features

The paper shows that sparse microbiome features can become phenotype-associated after compositional transformations like CLR, challenging claims that this indicates information leakage.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

DEBIAS-M corrects processing bias in microbiome data, improving cross-study generalization of prediction models by learning interpretable bias-correction factors.

Early prediction of preeclampsia using the first trimester vaginal microbiome

This study predicts preeclampsia using first trimester vaginal microbiome data with machine learning, achieving an auROC of 0.78 in the training set and 0.80 in an independent cohort.

Metagenomic coverage bias at transcription start sites is correlated with gene expression

The paper identifies coverage bias at transcription start sites in metagenomic data that correlates with gene expression, independent of GC bias and sequencing artifacts.

Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome

This study identifies vaginal metabolites associated with spontaneous preterm birth and shows they can predict risk with high accuracy using machine learning.

Accurate and robust inference of microbial growth dynamics from metagenomic sequencing

The paper introduces CoPTR, a tool for computing peak-to-trough ratios from metagenomic data, showing it is more accurate and provides more estimates than existing methods, and demonstrates its application in a case-control study of irritable bowel disease.

Environmental factors dominate over host genetics in shaping human gut microbiota composition

This study shows environmental factors have a greater impact on human gut microbiota than host genetics, with microbiome data adding significant predictive value to phenotypes.