AI Medical Compendium Topic:
Models, Molecular

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A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

Bioinformatics (Oxford, England)
MOTIVATION: Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein struct...

SVMQA: support-vector-machine-based protein single-model quality assessment.

Bioinformatics (Oxford, England)
MOTIVATION: The accurate ranking of predicted structural models and selecting the best model from a given candidate pool remain as open problems in the field of structural bioinformatics. The quality assessment (QA) methods used to address these prob...

NeBcon: protein contact map prediction using neural network training coupled with naïve Bayes classifiers.

Bioinformatics (Oxford, England)
MOTIVATION: Recent CASP experiments have witnessed exciting progress on folding large-size non-humongous proteins with the assistance of co-evolution based contact predictions. The success is however anecdotal due to the requirement of the contact pr...

ProQ3D: improved model quality assessments using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: Protein quality assessment is a long-standing problem in bioinformatics. For more than a decade we have developed state-of-art predictors by carefully selecting and optimising inputs to a machine learning method. The correlation has increase...

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of frag...

QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.

Bioinformatics (Oxford, England)
MOTIVATION: Protein model quality assessment (QA) plays a very important role in protein structure prediction. It can be divided into two groups of methods: single model and consensus QA method. The consensus QA methods may fail when there is a large...

Controlled regular locomotion of algae cell microrobots.

Biomedical microdevices
Algae cells can be considered as microrobots from the perspective of engineering. These organisms not only have a strong reproductive ability but can also sense the environment, harvest energy from the surroundings, and swim very efficiently, accommo...

5-Year Trends in QSAR and its Machine Learning Methods.

Current computer-aided drug design
BACKGROUND: Quantitative Structure-Activity Relationships (QSAR) is a well-established branch of computational chemistry. The presence of QSAR papers is decreasing for the last few years.

VH-VL orientation prediction for antibody humanization candidate selection: A case study.

mAbs
Antibody humanization describes the procedure of grafting a non-human antibody's complementarity-determining regions, i.e., the variable loop regions that mediate specific interactions with the antigen, onto a β-sheet framework that is representative...

Terpenoids and Steroids from Euphorbia hypericifolia.

Natural product communications
Two new triterpenoids and two new sterols, named euphyperins A-D (1-4), including an oleanane-type triterpenoid (1), a lupane-type nortriterpenoid (2), and two cholestane-type steroids (3 and 4), along with five known compounds (5-9) were isolated fr...