scispace - formally typeset
N

Nilesh Vaidya

Researcher at Princeton University

Publications -  11
Citations -  2211

Nilesh Vaidya is an academic researcher from Princeton University. The author has contributed to research in topics: Ribozyme & RNA. The author has an hindex of 8, co-authored 11 publications receiving 1648 citations. Previous affiliations of Nilesh Vaidya include Portland State University.

Papers
More filters
Journal ArticleDOI

Coexisting Liquid Phases Underlie Nucleolar Subcompartments

TL;DR: It is shown that subcompartments within the nucleolus represent distinct, coexisting liquid phases that may facilitate sequential RNA processing reactions in a variety of RNP bodies, and suggested that phase separation can give rise to multilayered liquids.
Journal ArticleDOI

RNA transcription modulates phase transition-driven nuclear body assembly

TL;DR: The assembly dynamics of liquid-phase nuclear bodies are quantified and find that they can be explained by classical models of phase separation and coarsening, and rRNA transcription and other nonequilibrium biological activity can modulate the effective thermodynamic parameters governing nucleolar and END assembly, but do not appear to fundamentally alter the passive phase separation mechanism.
Journal ArticleDOI

Spontaneous network formation among cooperative RNA replicators

TL;DR: It is shown that mixtures of RNA fragments that self-assemble into self-replicating ribozymes spontaneously form cooperative catalytic cycles and networks, indicating an intrinsic ability of RNA populations to evolve greater complexity through cooperation.
Journal ArticleDOI

Biophysical characterization of organelle-based RNA/protein liquid phases using microfluidics.

TL;DR: A microfluidic platform is introduced that drives protein droplets into a single large phase, which facilitates viscosity measurements using passive microrheology and/or active two-phase flow analysis, which enables studying the impact of ATP-dependent biological activity on RNP droplets, which is a key area for future research.
Journal ArticleDOI

Recycling of Informational Units Leads to Selection of Replicators in a Prebiotic Soup

TL;DR: Computational Monte Carlo studies indicate that a moderate level of recycling activity, spontaneous or catalyzed, leads to the most robust selection scenarios, and show that mixtures of scrambled and/or deleteriously mutated molecules can recycle their component fragments to generate fully functional recombinase ribozymes.