Peter O. Fedichev

This paper uses a dynamical systems model to explain how late-life lifespan extension in C. elegans occurs through changes in regulatory network stability rather than reversing damage.

HARVEST extracts structured bioactivity data from pharmaceutical patents using AI, producing millions of records and revealing gaps in existing databases.

The paper tracks aging in sled dogs using a variational autoregressive model to show that lamivudine temporarily decelerates DNA methylation clocks but not long-term biological age.

The paper introduces a minimal model of aging that predicts two regimes and guides intervention strategies for extending healthspan and lifespan.

ProtoBind-Diff generates novel, chemically valid ligands based on protein sequences without structural data, performing well in docking and binding affinity evaluations.

The paper uses graph neural networks to predict polypharmacological compounds that extend lifespan in C. elegans, finding 70% of selected compounds significantly increase lifespan.

The paper identifies thermodynamic control variables that regulate healthspan and maximum lifespan using DNA methylation data from mammals.

The paper analyzes DNA methylation and electronic health records to show aging is driven by entropy and configuration changes, with implications for age reversal.

The paper identifies two DNAm aging signatures in mice, one exponential and one linear, showing differential responses to longevity interventions like caloric restriction and parabiosis.

This paper develops a deep learning model to identify a blood-based biomarker of aging in mice using phenotypic data, finding it correlates with aging hallmarks and predicts lifespan.

The paper analyzes longitudinal blood marker data to show aging is associated with declining physiological resilience and predicts a lifespan limit around 120-150 years.

This study identifies a metabolic shift driven by PFKFB3 in CLN7 disease, showing that targeting glycolysis can alleviate disease hallmarks in a mouse model and patient-derived cells.

This study shows that the burden of rare protein-truncating variants negatively impacts human healthspan and lifespan in large cohorts.

This study shows that inhibiting PFKFB3 in neurons prevents redox stress and neuronal death in ischemia-reperfusion injury, and reduces brain damage in mice.

The paper identifies a universal transcriptomic signature of aging in C. elegans and shows it can predict lifespan extension and drug effects.

The paper investigates biological age modeling using supervised learning techniques, finding that biological aging acceleration correlates with disease burden and molecular markers of stress in both healthy and diseased individuals.

The paper quantifies biological age and frailty using locomotor activity data from NHANES and UKB, linking aging trajectories to mortality and health outcomes.

This study compares biological age models using NHANES data, finding that supervised models improve age estimation but reduce mortality prediction accuracy, and introduces a new mortality risk model.

This paper shows that the Strehler-Mildvan correlation arises from fitting degeneracy in Gompertz models, not from biological homogeneity, and demonstrates this through analysis of C. elegans survival data.