AIMC Topic: Proteins

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isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection.

Artificial intelligence in medicine
The Golgi Apparatus (GA) is a key organelle for protein synthesis within the eukaryotic cell. The main task of GA is to modify and sort proteins for transport throughout the cell. Proteins permeate through the GA on the ER (Endoplasmic Reticulum) fac...

Computational Intelligence for Medical Imaging Simulations.

Journal of medical systems
This paper describes how to simulate medical imaging by computational intelligence to explore areas that cannot be easily achieved by traditional ways, including genes and proteins simulations related to cancer development and immunity. This paper ha...

Different protein-protein interface patterns predicted by different machine learning methods.

Scientific reports
Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns ...

Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12.

Proteins
We develop two complementary pipelines, "Zhang-Server" and "QUARK", based on I-TASSER and QUARK pipelines for template-based modeling (TBM) and free modeling (FM), and test them in the CASP12 experiment. The combination of I-TASSER and QUARK successf...

Drug target ontology to classify and integrate drug discovery data.

Journal of biomedical semantics
BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research...

Glypre: In Silico Prediction of Protein Glycation Sites by Fusing Multiple Features and Support Vector Machine.

Molecules (Basel, Switzerland)
Glycation is a non-enzymatic process occurring inside or outside the host body by attaching a sugar molecule to a protein or lipid molecule. It is an important form of post-translational modification (PTM), which impairs the function and changes the ...

Specific and intrinsic sequence patterns extracted by deep learning from intra-protein binding and non-binding peptide fragments.

Scientific reports
The key finding in the DNA double helix model is the specific pairing or binding between nucleotides A-T and C-G, and the pairing rules are the molecule basis of genetic code. Unfortunately, no such rules have been discovered for proteins. Here we sh...

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

Proteins
In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on co...

Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.

Journal of theoretical biology
Predicting protein subcellular location with support vector machine has been a popular research area recently because of the dramatic explosion of bioinformation. Though substantial achievements have been obtained, few researchers considered the prob...

Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.

Proteins
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted resid...