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This study designs gene regulatory networks to slow somatic evolution in simplified multicellular organisms and identifies tradeoffs between network robustness and fitness.

The paper introduces a uniform method for inferring regulatory networks across cancer subtypes, showing it is adequate for multi-cohort analysis despite not being statistically superior.

This study shows that combining apple pectin and cellulose in zebrafish diets leads to non-additive gut microbiome changes and lasting intestinal barrier effects.

The paper introduces LADD to measure lineage path deviations from inferred developmental dynamics in single-cell RNA-seq data and finds lineages move faster than optimal paths.

The paper introduces mE-DIA, a multi-enzyme DIA-MS workflow that improves proteoform detection in proteomics by integrating analysis and interpretation into a single toolset.

The paper introduces PRISM to select low-fidelity simulators for multi-fidelity inference in vertex models, finding that early stopping is unreliable while coarser timesteps are effective.

The paper shows that the source of annotation data significantly affects the quality of automatically reconstructed genome-scale metabolic models.

This study shows that G1 phase cells exhibit stronger EMT gene expression and RNA velocity than cycling cells, suggesting cell cycle phase influences EMT and should not be regressed out.

This paper constructs a single-cell transcriptomic atlas of the pigtail macaque lung, revealing high similarity to human lung cell types and providing a reference for studying respiratory diseases in a translational model.

This study maps human lung fibrosis in 3D, showing how structural changes in tissue microarchitecture drive maladaptive repair states and disease progression.

This paper introduces a three-factor mathematical model to explain symmetry breaking and the n-1 rule in X-chromosome inactivation by integrating Xist, an X-linked activator, and SPEN.

The paper develops a proteomics-based machine learning workflow to identify cell-type-specific protein complexes in mouse embryonic stem cells, revealing 3,986 complexes and 1,388 unique interactions specific to mESC.

This paper introduces GEM-CM, a computational framework that couples reaction-diffusion models with genome-scale metabolic models to simulate Pseudomonas aeruginosa growth and pyocyanin production in agar gels.

This study uses a dynamical model to show how antibiotic exposure dynamics select for different gene regulatory strategies in resistance.

This paper uses photographs of mice to predict biological age and finds that older appearance correlates with frailty and shorter survival.

This paper develops a live bacterial system to reduce nicotine levels in blood and brain by enzymatic degradation in the gut, showing potential for non-systemic treatment of nicotine addiction.

This paper develops a theoretical framework to analyze cardiac-autonomic regulation using dynamical systems theory and demonstrates its properties through simulations.

This study examines how C. glutamicum cells respond to pH stress by tracking cell size and survival, revealing stochastic and heritable differences in acid and alkaline stress survival.

The paper models cell identity stability using a Markov framework, showing how mixing, competence, and commitment influence transition rates and proposes experiments to test these mechanisms.

This study builds a 3D mathematical model of adipose tissue showing complex architectures emerge from simple mechanical rules, suggesting mechanical forces drive tissue structure more than genetic programs.