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Gathering the most information by picking the least amount of data is a common task in experimental design or when exploring an unknown environment in reinforcement learning and robotics. A widely used measure for quantifying the…
Compositional data have two unique characteristics compared to typical multivariate data: the observed values are nonnegative and their summand is exactly one. To reflect these characteristics, a specific regularized regression model with…
Most genome assemblers construct point estimates, choosing a genome sequence from among many alternative hypotheses that are supported by the data. We present a Markov Chain Monte Carlo approach to sequence assembly that instead generates…
Genome sequencing is the basis for many modern biological and medicinal studies. With recent technological advances, metagenomics has become a problem of interest. This problem entails the analysis and reconstruction of multiple DNA…
Metagenomic taxonomic annotation aims to identify the microbial origins of DNA fragments in environmental samples. Traditional methods that rely on sequence similarity are often constrained by the high microbial diversity and the…
Advances in data collecting technologies in genomics have significantly increased the need for tools designed to study the genetic basis of many diseases. Effective statistical methods should excel in both prediction accuracy and biomarker…
Multicellular systems play a key role in bioprocess and biomedical engineering. Cell ensembles encountered in these setups show phenotypic variability like size and biochemical composition. As this variability may result in undesired…
Metagenomic studies have primarily relied on de novo assembly for reconstructing genes and genomes from microbial mixtures. While reference-guided approaches have been employed in the assembly of single organisms, they have not been used in…
Analyzing multivariate count data generated by high-throughput sequencing technology in microbiome research studies is challenging due to the high-dimensional and compositional structure of the data and overdispersion. In practice,…
Integrative modeling of macromolecular assemblies allows for structural characterization of large assemblies that are recalcitrant to direct experimental observation. A Bayesian inference approach facilitates combining data from…
The success of metabolomics studies depends upon the "fitness" of each biological sample used for analysis: it is critical that metabolite levels reported for a biological sample represent an accurate snapshot of the studied organism's…
Current advances in next generation sequencing techniques have allowed researchers to conduct comprehensive research on microbiome and human diseases, with recent studies identifying associations between human microbiome and health outcomes…
Metagenomics enables the reconstruction of microbial genomes in complex microbial communities without the need for culturing. Since assembly typically results in fragmented genomes the grouping of genome fragments (contigs) belonging to the…
Metagenomics has revealed hundreds of bacterial species in almost all microbiota. In a few well-studied cases, bacterial communities have been observed to coordinate their metabolic fluxes. In principle, bacteria can divide tasks to reap…
Nutrient gradients and limitations play a pivotal role in the life of all microbes, both in their natural habitat as well as in artificial, microfluidic systems. Spatial concentration gradients of nutrients in densely packed cell…
Generative molecular design has moved from proof-of-concept to real-world applicability, as marked by the surge in very recent papers reporting experimental validation. Key challenges in explainability and sample efficiency present…
The gut microbiome plays a crucial role in human health, yet the mechanisms underlying host-microbiome interactions remain unclear, limiting its translational potential. Recent microbiome multiomics studies, particularly paired…
Many practical applications of AI in medicine consist of semi-supervised discovery: The investigator aims to identify features of interest at a resolution more fine-grained than that of the available human labels. This is often the scenario…
While metagenomics has emerged as a technology of choice for analyzing bacterial populations, assembly of metagenomic data remains difficult thus stifling biological discoveries. metaSPAdes is a new assembler that addresses the challenge of…
The human microbiome plays an important role in human health and disease status. Next generating sequencing technologies allow for quantifying the composition of the human microbiome. Clustering these microbiome data can provide valuable…