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Melissa M. Pentony

Researcher at University College London

Publications -  6
Citations -  1323

Melissa M. Pentony is an academic researcher from University College London. The author has contributed to research in topics: Gene & Proteome. The author has an hindex of 5, co-authored 5 publications receiving 1254 citations. Previous affiliations of Melissa M. Pentony include Maynooth University & Birkbeck, University of London.

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Journal ArticleDOI

Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified

TL;DR: It is demonstrated that for two large datasets derived from the proteobacteria and archaea, one of the most favored models in both datasets is a model that was originally derived from retroviral Pol proteins.
Journal ArticleDOI

Does a tree-like phylogeny only exist at the tips in the prokaryotes?

TL;DR: The extent to which prokaryotic evolution has been influenced by horizontal gene transfer (HGT) and therefore might be more of a network than a tree is unclear and supertree methods are used to ask whether a definitive proKaryotic phylogenetic tree exists and whether it can be confidently inferred using orthologous genes.
Journal ArticleDOI

Insights into the regulation of intrinsically disordered proteins in the human proteome by analyzing sequence and gene expression data

TL;DR: The evidence suggests that the enrichment of signals for miRNA targeting and ubiquitination may help prevent the accumulation of disordered proteins in the cell.
Journal ArticleDOI

ISPIDER Central: an integrated database web-server for proteomics

TL;DR: The ISPIDER Central Proteomic Database search is presented, an integration service offering novel search capabilities over leading, mature, proteomic repositories including PRoteomics IDEntifications database (PRIDE), PepSeeker, PeptideAtlas and the Global Proteome Machine.
Book ChapterDOI

Computational Resources for the Prediction and Analysis of Native Disorder in Proteins

TL;DR: This chapter focuses on computational approaches to predicting such regions and analyzing the functions linked to them, and has implications for protein scientists who wish to study such properties as molecular recognition and post-translational modifications.