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Showing posts with the label artificial neural networks

Artificial neural networks-based approach to design ARIs using QSAR for diabetes mellitus

In this article, in the first part, we propose an artificial neural network-based intelligent technique to determine the quantitative structure-activity relationship (QSAR) among known aldose reductase inhibitors (ARIs) for diabetes mellitus using two molecular descriptors, i.e., the electronegativity and molar volume of functional groups present in the main ARI lead structure. We have shown that the multilayer perceptron-based model is capable of determining the QSAR quite satisfactorily, with high  R -value. Usually, the design of potent ARIs requires the use of complex computer docking and quantum mechanical (QM) steps involving excessive time and human judgement. In the second part of this article, to reduce the design cycle of potent ARIs, we propose a novel ANN technique to eliminate the computer docking and QM steps, to predict the total score. The MLP-based QSAR models obtained in the first part are used to predict the potent ARIs, using the experimental data reported by Hu...

The Brain Machine Interface

Dr. Justin Sanchez discusses technologies that enable direct brain to computer interfacing, Dr. Justin C. Sanchez , Director of the Neuroprosthetics Research Group, Assistant Professor, Department of Pediatrics, Division of Neurology, Department of Neuroscience, Department of Biomedical Engineering, University of Florida. I really had no idea that the technologies that Justin has developed existed other than in science fiction. The possibilities are endless, and could change everything from computing, to flying planes, to simply changing the channel… Do you want to know more? Listen to Dr. Justin Sanchez! Be a part of the XTractor community. XTractor is the first of its kind - Literature alert service , that provides manually curated and annotated sentences for the Keywords of user preference. XTractor maps the extracted entities (genes, processes, drugs, diseases etc) to multiple ontologies and enables customized report generation. With XTractor the sentences are categorized into ...

Certain HIV treatment less effective when used with anti-TB therapy

Combination antiretroviral therapy (ART) is frequently initiated in resource-limited countries when patients are being treated for tuberculosis. Co-administration of ART and anti-tubercular therapy may be complicated by shared toxicity or adverse drug interactions, according to background information in the article. Rifampicin-based anti-tubercular therapy reduces the plasma concentrations of the antiretroviral agents efavirenz and nevirapine. The virological consequences of these interactions are not well known. Do you want to know more? Be a part of the XTractor community. XTractor is the first of its kind - Literature alert service , that provides manually curated and annotated sentences for the Keywords of user preference. XTractor maps the extracted entities (genes, processes, drugs, diseases etc) to multiple ontologies and enables customized report generation. With XTractor the sentences are categorized into biological significant relationships and it also provides the user w...

Computational intelligence approaches for pattern discovery in biological systems

Natural Selection, Inc. is a very interesting find that i came across after reading through a publication in Oxford journals. This company has unique expertise in computational intelligence applied to bioinformatics problems. Led by Dr. Gary Fogel. The bioinformatics team there has developed a suite of computational tools for small molecule lead discovery and optimization. Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key...