Victor Olariu

Hic2 fast-tracks iPS cell generation by suppressing KLF4-dependent epidermal detour

This paper identifies Hic2 as a gene that enhances iPSC generation by suppressing KLF4-dependent epidermal gene expression during reprogramming.

Generating human parvalbumin interneurons through 3D glia reprogramming

This paper describes a method to generate human parvalbumin interneurons from glial precursor cells using direct reprogramming and identifies a distinct transcriptional profile and reprogramming trajectory.

T-cell commitment inheritance - an agent-based multi-scale model

The paper develops an agent-based model to study T-cell commitment timing and inheritance, showing a three-step process with transcriptional preparation, loss of Bcl11b-opposing function, and DN2b state transition.

CELLoGeNe - an Energy Landscape Framework for Logical Networks Controlling Cell Decisions

CELLoGeNe maps Boolean gene regulatory networks into energy landscapes to analyze cell fate decisions, identifying attractors in pluripotency maintenance and reprogramming.

Neural tube patterning: from a minimal model for rostrocaudal patterning towards an integrated 3D model

The paper presents a minimal gene regulatory model for rostrocaudal neural tube patterning and integrates it with a dorsoventral model to predict 3D patterning and sensitivity to morphogen levels.

A Quantitative Model of Cellular Decision Making in Direct Neuronal Reprogramming

This study develops a quantitative model of gene regulatory interactions in neuronal reprogramming, showing that PTB and nPTB interactions are critical for predicting reprogramming outcomes.

Multi-scale dynamical modelling of T-cell development from an early thymic progenitor state to lineage commitment

The paper develops a multi-scale dynamic model of T-cell development, incorporating gene regulatory networks, epigenetic gates, and proliferation kinetics to simulate commitment dynamics.

Revisiting the erythroid-myeloid lineage decision - a data-driven dynamical model analysis

The paper uses a dynamical model to analyze gene regulatory networks and suggests GATA2 drives erythroid lineage specification by repressing PU.1, while GATA1 is more involved in downstream differentiation.