scispace - formally typeset
R

Robin D. Knight

Researcher at Princeton University

Publications -  16
Citations -  8021

Robin D. Knight is an academic researcher from Princeton University. The author has contributed to research in topics: Genetic code & Transfer RNA. The author has an hindex of 15, co-authored 16 publications receiving 7227 citations. Previous affiliations of Robin D. Knight include University of Colorado Boulder.

Papers
More filters
Journal ArticleDOI

Obesity alters gut microbial ecology

TL;DR: Analysis of the microbiota of genetically obese ob/ob mice, lean ob/+ and wild-type siblings, and their ob/+ mothers, all fed the same polysaccharide-rich diet, indicates that obesity affects the diversity of the gut microbiota and suggests that intentional manipulation of community structure may be useful for regulating energy balance in obese individuals.
Journal ArticleDOI

Evolution of symbiotic bacteria in the distal human intestine.

TL;DR: In this article, the authors examined how the intestinal environment affects microbial genome evolution and found that lateral gene transfer, mobile elements, and gene amplification have played important roles in affecting the ability of gut-dwelling Bacteroidetes to vary their cell surface, sense their environment, and harvest nutrient resources present in the distal intestine.
Journal ArticleDOI

Rewiring the keyboard: evolvability of the genetic code

TL;DR: The distribution and causes of secondary deviations from the canonical genetic code are examined, with the majority of non-standard codes arise from alterations in the tRNA, with most occurring by post-transcriptional modifications, such as base modification or RNA editing, rather than by substitutions within tRNA anticodons.
Journal ArticleDOI

A simple model based on mutation and selection explains trends in codon and amino-acid usage and GC composition within and across genomes.

TL;DR: It is shown here that a simple model of processes acting at the nucleotide level explains codon usage across a large sample of species and quantitatively predicts responses of individual codons and amino acids to genome composition.
Journal ArticleDOI

Early Fixation of an Optimal Genetic Code

TL;DR: It is shown that if theoretically possible code structures are limited to reflect plausible biological constraints, and amino acid similarity is quantified using empirical data of substitution frequencies, the canonical code is at or very close to a global optimum for error minimization across plausible parameter space.