Department of Mathematics, UW-Madison, Madison, USA.
Published: January 2020
AI Article Synopsis
Article Abstract
In evolutionary biology, the speciation history of living organisms is represented graphically by a phylogeny, that is, a rooted tree whose leaves correspond to current species and whose branchings indicate past speciation events. Phylogenetic analyses often rely on molecular sequences, such as DNA sequences, collected from the species of interest, and it is common in this context to employ statistical approaches based on stochastic models of sequence evolution on a tree. For tractability, such models necessarily make simplifying assumptions about the evolutionary mechanisms involved. In particular, commonly omitted are insertions and deletions of nucleotides-also known as indels. Properly accounting for indels in statistical phylogenetic analyses remains a major challenge in computational evolutionary biology. Here, we consider the problem of reconstructing ancestral sequences on a known phylogeny in a model of sequence evolution incorporating nucleotide substitutions, insertions and deletions, specifically the classical TKF91 process. We focus on the case of dense phylogenies of bounded height, which we refer to as the taxon-rich setting, where statistical consistency is achievable. We give the first explicit reconstruction algorithm with provable guarantees under constant rates of mutation. Our algorithm succeeds when the phylogeny satisfies the "big bang" condition, a necessary and sufficient condition for statistical consistency in this setting.
The neural crest (NC) is an embryonic cell population with high migratory capacity. It contributes to forming several organs and tissues, such as the craniofacial skeleton and the peripheral nervous system of vertebrates. Both pre-migratory and post-migratory NC cells are plastic, adopting multiple differentiation paths by responding to different inductive environmental signals.
Foundational techniques in molecular biology-such as cloning genes, tagging biomolecules for purification or identification, and overexpressing recombinant proteins-rely on introducing non-native or synthetic DNA sequences into organisms. These sequences may be recognized by the transcription and translation machinery in their new context in unintended ways. The cryptic gene expression that sometimes results has been shown to produce genetic instability and mask experimental signals.
(Illiciaceae), an ecologically significant endemic plant, predominantly grows in Guangxi, China, which is the primary region for its cultivation. This area accounts for more than 80% of the total cultivation and yield in China. Despite its importance, comprehensive studies on the chloroplast (cp) genome of are limited.
DNA repair is a most important cellular process that helps maintain the integrity of the genome and is currently considered by researchers as one of the factors determining the maximum lifespan. The central regulator of the DNA repair process is the enzyme poly(ADP-ribose)polymerase 1 (PARP1). PARP1 catalyzes the synthesis of poly(ADP-ribose) polymer (PAR) upon DNA damage using nicotinamide adenine dinucleotide (NAD+) as a substrate.
Peptides, due to their diverse and controllable properties, are used as both liquid and gas phase recognition elements for both biological and chemical targets. While it is well understood how binding of a peptide to a biomolecule can be converted into a sensing event, there is not the same mechanistic level of understanding with regard to how peptides modulate the selectivity of semiconductor/conductor-based gas sensors. Notably, a rational, mechanistic study has not yet been performed to correlate peptide properties to the sensor response for volatile organic compounds (VOCs) as a function of chemical properties.
