Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 7th International Me Riccardo Rizzo,Paulo J. G. Lisboa Conference

PTCA635

De Novo Protein Subcellular Localization Prediction by N-to-1 Neural Networkshe post-genomic era, fast and accurate predictors of subcellular location are required if this abundance of sequence data is to be fully exploited. We have developed a subcellular localization predictor (SCL_pred) which predicts the location of a protein into four classes for animals and fungi and f

Microgram

Osmoprotectants in the Sugarcane (, spp.) Transcriptome Revealed by in Silico Evaluationrotectants in most organisms, including plants. In the present work, a search of known osmoprotectants (., ., ., ., ., ., ., . and .) was carried out in the sugarcane transcriptome (237,954 expressed sequence tags) using . procedures. Alignments revealed that sugarcane presents a high number of osmo

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青春期

Identification and Expression of Early Nodulin in Sugarcane Transcriptome Revealed by in Silico Analns in non-legumes, including monocot plants, suggesting that these genes play additional roles besides nodulation. The presence and expression profile of the early nodulin genes (., ., ., ., ., and .) was evaluated in the sugarcane transcriptome (237,954 ESTs) using in silico procedures. 129 sugarca

邊緣帶來(lái)墨水

An Interactive Method of Anatomical Segmentation and Gene Expression Estimation for an Experimental of anatomical segmentation of a histological brain slice and estimation of slice’s gene expression level. The first problem is solved by interactive registration of an experimental brain slice into 3D brain model constructed using Allen Brain Atlas. The second problem is solved by special image fil

hemoglobin

Prediction of the Bonding State of Cysteine Residues in Proteins with Machine-Learning Methodsequences. This task is the first step for the identification of disulfide bonds in proteins. We score the performance of three different approaches: 1) Hidden Support Vector Machines (HSVMs) which integrate the SVM predictions with a Hidden Markov Model; 2) SVM-HMMs which discriminatively train mode

phlegm

Supervised Classification Methods for Mining Cell Differences as Depicted by Raman Spectroscopyient technologies or tedious one-by-one empirical examination of the cells. Recently, Raman spectroscopy, a inexpensive and efficient method, has been employed for cell discrimination. Nevertheless, the traditional protocols for analyzing Raman spectra require preprocessing and peak fitting analysis

itinerary

Use of Biplots and Partial Least Squares Regression in Microarray Data Analysis for Assessing Associ genes..Visualization techniques and Partial Least Squares (PLS) regression have thus gained relevance in genomic. Biplots provide an aid to understand relationships between genes and samples and among genes, whereas passive projections of variables are helpful for understanding conditional relation

Infiltrate

Qualitative Reasoning on Systematic Gene Perturbation Experimentsgenes. For this purpose, we present a novel Qualitative Reasoning approach, based on a qualitative abstraction of DNA-microarray data and on a set of IF-THEN inference rules. Our algorithm exhibits an extremely low rate of false positives, competitive with the state-of-the-art, on both noise-free an

outskirts

Biclustering by Resamplingut an explicit information about it. In many cases researchers use analysis methodologies such as clustering to classify data with respect to the patterns and conditions together. But in the last few years new analysis tool such as a biclustering were proposed and applied to the many specific proble