Sergej Andrejev

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

The paper introduces vampW, a Bayesian method for joint variable selection in omic biomarkers and time-to-event data, showing reduced false discoveries and improved prediction.

Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes

This study develops a parallelized ALE platform to evolve wine yeasts with enhanced metabolic traits, finding that expanded replicates and lineages improve the chances of evolving improved strains with desirable industrial performance.

Emergent survival and extinction of species within gut bacterial communities

The paper shows how species in gut bacterial communities can survive or go extinct based on resource availability and metabolic interactions, identifying emergent survival and community-driven extinctions.

Linear Interaction Between Replication and Transcription Shapes DNA Break Dynamics at Recurrent DNA Break Clusters

The paper investigates DNA break dynamics at recurrent DNA break clusters (RDCs) in mouse neural progenitor cells, revealing how replication-transcription collisions influence DSB formation and orientation.

Predictive evolution of metabolic phenotypes using model-designed selection niches

This paper predicts the evolution of fitness-costly traits by designing selection niches using metabolic models and validates it in yeast for increased aroma compound secretion.

Bioactivity assessment of natural compounds using machine learning models based on drug target similarity

This paper develops a machine learning model to predict protein targets of natural compounds based on drug target similarity, identifying potential therapeutics with experimental validation.

Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

CarveMe automates the reconstruction of genome-scale metabolic models for microbial species and communities, achieving performance comparable to manual curation.