3 resultados para Grey Level Co-occurrence Matrix

em National Center for Biotechnology Information - NCBI


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Tham Khuyen Cave (Lang Son Province, northern Vietnam) is one of the more significant sites to yield fossil vertebrates in east Asia. During the mid-1960s, excavation in a suite of deposits produced important hominoid dental remains of middle Pleistocene age. We undertake more rigorous analyses of these sediments to understand the fluvial dynamics of Pleistocene cave infilling as they determine how skeletal elements accumulate within Tham Khuyen and other east Asian sites. Uranium/thorium series analysis of speleothems brackets the Pleistocene chronology for breaching, infilling, and exhuming the regional paleokarst. Clast analysis indicates sedimentary constituents, including hominoid teeth and cranial fragments accumulated from very short distances and under low fluvial energy. Electron spin resonance analysis of vertebrate tooth enamel and sediments shows that the main fossil-bearing suite (S1-S3) was deposited about 475 thousand years ago. Among the hominoid teeth excavated from S1-S3, some represent Homo erectus and Gigantopithecus blacki. Criteria are defined to differentiate these teeth from more numerous Pongo pygmaeus elements. The dated co-occurrence of Homo erectus and Gigantopithecus blacki at Tham Khuyen helps to establish the long co-existence of these two species throughout east Asia during the Early and Middle Pleistocene.

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As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing ‘global views’ of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein–protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein–protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V–b, for attribute value V and constant exponent b), with a few folds having large values and most having small values.

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Although much of the brain’s functional organization is genetically predetermined, it appears that some noninnate functions can come to depend on dedicated and segregated neural tissue. In this paper, we describe a series of experiments that have investigated the neural development and organization of one such noninnate function: letter recognition. Functional neuroimaging demonstrates that letter and digit recognition depend on different neural substrates in some literate adults. How could the processing of two stimulus categories that are distinguished solely by cultural conventions become segregated in the brain? One possibility is that correlation-based learning in the brain leads to a spatial organization in cortex that reflects the temporal and spatial clustering of letters with letters in the environment. Simulations confirm that environmental co-occurrence does indeed lead to spatial localization in a neural network that uses correlation-based learning. Furthermore, behavioral studies confirm one critical prediction of this co-occurrence hypothesis, namely, that subjects exposed to a visual environment in which letters and digits occur together rather than separately (postal workers who process letters and digits together in Canadian postal codes) do indeed show less behavioral evidence for segregated letter and digit processing.