Titlebook: Computational Intelligence in Medical Informatics; Naresh Babu Muppalaneni,Vinit Kumar Gunjan Book 2015 The Author(s) 2015 Alpha-Dystrogly

松果

,Structural Insights into IbpA–IbpB Interactions to Predict Their Roles in Heat Shock Response,ic α-crystalline domain. It is known that the cooperation between IbpA and IbpB is crucial for their chaperone activity in heat stressed condition. So far, the molecular mechanisms of the stress response of the IbpA/IbpB protein system have not been well understood. In the present work, an attempt h

宣誓書(shū)

Improving the Performance of Multi-parameter Patient Monitor System Using Additional Features, In this work, we present the results of the MPM using the SVM as back-end classifier. Further, we use correlation features (feature expansion) along with base parameters in an effort to improve the performance of MPM and note that the performance of the MPM enhanced significantly.

終點(diǎn)

Effect of Feature Selection on Kinase Classification Models,nder the ROC Curve (AUC). The method identifies the feature subset from the datasets which contains the physiochemical properties of kinases like amino acid, dipeptide, and pseudo amino acid composition. An improvised performance of classification is noted for feature subset than with all the featur

慢慢流出

一致性

Calin Valsan,Elena Druica,Rodica Ianole We predicted the structure of the DsrO protein obtained by homology modeling. The structure of the modeled protein was then docked with various sulfur anion ligands to understand the molecular mechanism of the transportation process of sulfur anion ligands by this DsrMKJOP complex. This study may t

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Aggressive

Cubicle

Abdelnaser Omran,Odile Schwarz-Herion In this work, we present the results of the MPM using the SVM as back-end classifier. Further, we use correlation features (feature expansion) along with base parameters in an effort to improve the performance of MPM and note that the performance of the MPM enhanced significantly.

contradict

Ambulatory

The Real Generators of the Unitary Group of signature molecules related to RA. The statistical analysis was performed using false discovery rate (FDR), t-test, one-way anova, and Pearson correlation with favorable p-value. The K-core analysis depicted the change in network topology which consisted of up- and downregulated genes network, r