1,720,972 research outputs found
Cavity Detection and Matching for Binding Site Recognition
No full textAbstractWe developed a suite of methods for the problem of protein binding site recognition, based on a representation of the protein structures by a collection of spin-images. A procedure for cavity detection is coupled with a method previously developed for the recognition of similar regions in two proteins, and applied to the comparison of two protein’s cavities, the all-to-all pairwise comparison of a set of cavities, and the recognition of multiple binding sites in one cavity. All the presented methods can be used to screen large collections of proteins.The detection of cavities in a given protein is often the preliminary step in protein binding site recognition, since binding sites usually lie in cavities. The comparison of two cavities identifies two similar regions in the two cavities, and hints at a common functional structure when one or both regions include a binding site. The all-to-all pairwise comparison of a set of cavities is clustered according to the measure of similarity of the cavities, obtaining a clustering that groups together cavities with the same binding sites, when their structures are similar enough. Recognition of multiple binding sites in one cavity is performed by the comparison of a cavity, called background cavity, with a dataset of cavities, and clustering its residues that match the residues of other cavities in the data set. The four methods are benchmarked on different databases, and their effectiveness is discussed
MolLoc: a web tool for the local alignment of molecular surfaces
No full textMolLoc stands for Molecular Local surface comparison, and is a web server for the structural comparison of molecular surfaces. Given two structures in PDB format, the user can compare their binding sites, cavities or any arbitrary residue selection. Moreover, the web server allows the comparison of a query structure with a list of structures. Each comparison produces a structural alignment that maximizes the extension of the superimposition of the surfaces, and returns the pairs of atoms with similar physicochemical properties that are close in space after the superimposition. Based on this subset of atoms sharing similar physicochemical properties a new rototranslation is derived that best superimposes them. MolLoc approach is both local and surface-oriented, and therefore it can be particularly useful when testing if molecules with different sequences and folds share any local surface similarity. The MolLoc web server is available at http://bcb.dei.unipd.it/MolLoc
Monotony of Surprise and Large Scale Quest for Unusual Words
No full textThe problem of characterizing and detecting recurrent sequence patterns such as substrings or motifs and related associations or rules is variously pursued in order to compress data, unveil structure, infer succinct descriptions, extract and classify features, etc. In molecular biology, exceptionally frequent or rare words in bio-sequences have been implicated in various facets of biological function and structure. The discovery, particularly on a massive scale, of such patterns poses interesting methodological and algorithmic problems and often exposes scenarios in which tables and synopses grow faster and bigger than the raw sequences they are meant to encapsulate. In previous study, the ability to succinctly compute, store, and display unusual substrings has been linked to a subtle interplay between the combinatorics of the subword of a word and local monotonicities of some scores used to measure the departure from expectation. In this paper, we carry out an extensive analysis of such monotonicities for a broader variety of scores. This supports the construction of data structures and algorithms capable of performing global detection of unusual substrings in time and space linear in the subject sequences, under various probabilistic models
Linear Global Detectors of Redundant and Rare Strings
Get PDFThe identification of strings that are, by some measure, redundant or rare in the context of larger sequences is an implicit goal of any data compression method. In the straightforward approach to searching for unusual substrings, the words (up to a certain length) are enumerated more or less exhaustively and individually checked in terms of observed and expected frequencies, variances, and scores of discrepancy and significance thereof. As is well known, clever methods are available to compute and organize the counts of occurrences of all substrings of a given string. The corresponding tables take up the tree-like structure of a special kind of digital search index or trie. We show here that under several accepted measures of deviation from expected frequency, the candidate over- or under-represented words are restricted to the O(n) words that end at internal nodes of a compact suffix tree, as opposed to the Θ(n2) possible substrings. This surprising fact is a consequence of properties in the form that if a word that ends in the middle of an arc is, say, over-represented, then its extension to the nearest node of the tree is even more so. Based on this, we design global linear detectors of favoured and unfavored words for our probabilistic framework, and display the results of some preliminary that apply our constructions to the analysis of genomic sequence
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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