Raquel Cardoso de Melo Minardi

Protein cutoff scanning: A comparative analysis of cutoff dependent and cutoff free methods for prospecting contacts in proteins

In this study, we carried out a comparative analysis between two classical methodologies to prospect residue contacts in proteins: the traditional cutoff dependent (CD) approach and cutoff free Delaunay tessellation (DT). In addition, two alternative coarse‐grained forms to represent residues were tested: using alpha carbon (CA) and side chain geometric center (GC). A database was built, comprising three top classes: all alpha, all beta, and alpha/beta. We found that the cutoff value at about 7.0 Å emerges as an important distance parameter. Up to 7.0 Å, CD and DT properties are unified, which implies that at this distance all contacts are complete and legitimate (not occluded). We also have shown that DT has an intrinsic missing edges problem when mapping the first layer of neighbors. In proteins, it may produce systematic errors affecting mainly the contact network in beta chains with CA. The almost‐Delaunay (AD) approach has been proposed to solve this DT problem. We found that even AD may not be an advantageous solution. As a consequence, in the strict range up to 7.0 Å, the CD approach revealed to be a simpler, more complete, and reliable technique than DT or AD. Finally, we have shown that coarse‐grained residue representations may introduce bias in the analysis of neighbors in cutoffs up to 6.8 Å, with CA favoring alpha proteins and GC favoring beta proteins. This provides an additional argument pointing to the value of 7.0 Å as an important lower bound cutoff to be used in contact analysis of proteins. Proteins 2009.

GreenWiki: a tool to support users' assessment of the quality of Wikipedia articles

In this work, we present GreenWiki, which is a wiki with a panel of quality indicators to assist the reader of a Wikipedia article in assessing its quality.

uTrack: track yourself! monitoring information on online social media

The past one decade has witnessed an astounding outburst in the number of online social media (OSM) services, and a lot of these services have enthralled millions of users across the globe. With such tremendous number of users, the amount of content being generated and shared on OSM services is also enormous. As a result, trying to visualize all this overwhelming amount of content, and gain useful insights from it has become a challenge. In this work, we present uTrack, a personalized web service to analyze and visualize the diffusion of content shared by users across multiple OSM platforms. To the best of our knowledge, there exists no work which concentrates on monitoring information diffusion for personal accounts. Currently, uTrack monitors and supports logging in from Facebook, Twitter, and Google+. Once granted permissions by the user, uTrack monitors all URLs (like videos, photos, news articles) the user has shared in all OSM services supported, and generates useful visualizations and statistics from the collected data.

How to compute protein residue contacts more accurately

Computing contacts in proteins is important to several types of studies from Bioinformatics to Structural Biology. An accurate computation of contacts is essential to the correctness and reliability of applications involving folding prediction, protein structure prediction, quality assessment of protein structures, network contacts analysis, thermodynamic stability prediction, protein-protein and protein-ligand interactions, docking and so forth. In this work, we built an extensive database of contacts using about 45,000 structures from PDB to compare three paradigms for contact prospection at the atomic level: distance-based only, distance-geometry-based and distance-angulation-based. The main contribution of this paper is a critical evaluation of three different paradigms that can be used to compute contacts between protein atoms. We focused on protein-protein interfaces and analyzed four types of contacts, namely hydrogen bonds, aromatic stackings, hydrophobic and ionic (attractive) interactions. We scanned for possible contacts in the range from 0 to 7 Å. Our database with all computed contacts as well as the source code used to populate this database is freely available at bioinfo.dcc.ufmg.br/capri Our data showed the importance of a geometric approach to filter out spurious occluded contacts after about 3.5 Å for aromatic stackings, hydrophobic and ionic interactions. For hydrogen bonds, to filter out spurious contacts, we need to consider the angles involved in the interactions.