Nikos S. Hatzakis

This study shows that myosin I motor activities enhance lipid diffusion by converting low-speed lipids to high-speed and reducing confined and subdiffusive motion in actin-rich regions.

This study uses single-particle tracking to compare early entry checkpoints of SARS-CoV-2 G614 and BA.5 variants, revealing variant-specific differences in binding and internalization.

BioBrain translates natural language into reproducible microscopy analysis pipelines, outperforming language models in accuracy while enabling non-experts to analyze complex imaging data.

DNAsight automates AFM image analysis of chromatin organization, revealing protein-specific structural signatures and nucleosome spacing distributions.

APOSM improves generative small-molecule design by using pairwise preference learning to enhance surrogate model reliability and active candidate selection.

The paper shows that LD-targeted proteins are confined by nanodomains and transported via ER-LD bridges, revealing mechanisms for their selective accumulation on lipid droplets.

This study shows that tuning siRNA packing order in lipid nanoparticles improves functional delivery by enhancing silencing potency through less compact packing.

RNASCAPE quantifies mRNA cytosolic escape using deep learning, achieving 78% accuracy with three timepoints and LNP parameters, revealing cholesterol's impact on mRNA release.

MORPHIS quantifies single-cell morphological responses to treatments and aging, distinguishing compound-specific signatures and aging-related changes in Caco-2, HeLa, and C. elegans cells.

The paper uses machine learning and diffusion analysis to compare intracellular trafficking of insulin analogs and endogenous insulin, revealing differences in diffusion and lysosomal colocalization.

This study develops polymer-modified liposomes (PMLs) for drug delivery, showing size-dependent cargo packing and effective intracellular delivery of various cargoes including siRNA.

The paper shows CTCF controls chromatin boundary permeability through a dynamic conformational ensemble, not static occupancy, influencing cohesin capture probabilities.

This paper introduces DeepSPT, a deep learning framework that automates the analysis of sub-cellular diffusion to infer functional information, achieving high accuracy in identifying endosomal structures during viral infections.

This study synthesizes and characterizes pH and temperature responsive lipase-polymer biohybrids, showing increased enzymatic activity and stability compared to native lipases.

The paper shows that neurons have constitutive endolysosomal perforations enabling internalized alpha-synuclein fibrils to induce aggregation, and inhibiting PIKfyve kinase reduces this effect.

This paper introduces biomimetic graphitic carbon nitride nanoparticles that enable multiscale photo-modulation of cells and tissues through light-responsive mechanisms.

This study uses single-molecule assays to analyze how binding efficiency, processivity, and turnover affect protease activity in Savinase and its mutants.

This study tracks single nanoMOFs in live cells to understand their intracellular dynamics and internalization pathways using fluorescence and machine learning.

This paper evaluates how different performance metrics and generalization definitions affect the assessment of protein regression models.