✦ LIBER ✦

Disparate data fusion for protein phosphorylation prediction

✍ Scribed by Genetha A. Gray; Pamela J. Williams; W. Michael Brown; Jean-Loup Faulon; Kenneth L. Sale

Publisher: Springer US
Year: 2008
Tongue: English
Weight: 438 KB
Volume: 174
Category: Article
ISSN: 0254-5330
DOI: 10.1007/s10479-008-0347-9

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Bayesian analysis for fusion of data fro

Bayesian analysis for fusion of data from disparate imaging systems for surveillance

✍ G.D. Jones; R.E. Allsop; J.H. Gilby 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 224 KB

This paper investigates whether the segmentation of surveillance images can be improved by fusing low-spatial-resolution thermal data with high-spatial-resolution visual information. The context of this investigation is the surveillance of sterile zones where an alarm is required should a person ent

Comparing early and late data fusion met

Comparing early and late data fusion methods for gene expression prediction

✍ Matteo Re 📂 Article 📅 2010 🏛 Springer 🌐 English ⚖ 264 KB

Multi-stimuli multi-channel data and dec

Multi-stimuli multi-channel data and decision fusion strategies for dyslexia prediction using neonatal ERPs

✍ Hyunseok Kook; Lalit Gupta; Dennis Molfese; K.C. Fadem 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 223 KB

AutoMotif Server for prediction of phosp

AutoMotif Server for prediction of phosphorylation sites in proteins using support vector machine: 2007 update

✍ Dariusz Plewczynski; Adrian Tkacz; Lucjan S. Wyrwicz; Leszek Rychlewski; Krzyszt 📂 Article 📅 2007 🏛 Springer-Verlag 🌐 English ⚖ 143 KB

An information theoretic approach for im

An information theoretic approach for improving data driven prediction of protein model quality

✍ Alfonso Montuori; Giovanni Raimondo; Eros Pasero 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 778 KB

We present the results of an information theory-based approach to select an optimal subset of features for the prediction of protein model quality. The optimal subset of features was calculated by means of a backward selection procedure. The performances of a probabilistic classifier modeled by mean

QSAR models based on isomorphic and noni

QSAR models based on isomorphic and nonisomorphic data fusion for predicting the blood brain barrier permeability

✍ Manuel Urbano Cuadrado; Irene Luque Ruiz; Miguel Ángel Gómez-Nieto 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 472 KB

## Abstract A QSAR model for predicting the blood brain barrier permeability (BBBP) in a large and heterogeneous variety of compounds (136 compounds) has been developed using approximate similarity (AS) matrices as predictors and PLS as multivariate regression technique. AS values fuse information