The present study is to evaluate and compare the prediction and simulating efficiencies of response surface methodology (RSM) and artificial neural network (ANN) based models on fatty acid methyl esters (FAME) yield achieved from muskmelon oil (MMO) ...
Enzyme catalysis is one of the most essential and striking processes among of all the complex processes that have evolved in living organisms. Enzymes are biological catalysts, which play a significant role in industrial applications as well as in me...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Sep 22, 2014
In the present study, zinc sulfide nanoparticle loaded on activated carbon (ZnS-NP-AC) simply was synthesized in the presence of ultrasound and characterized using different techniques such as SEM and BET analysis. Then, this material was used for br...
Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vecto...
Pharmaceutical development and technology
Apr 24, 2014
Novel granulated pellets technique was adopted to prepare granulated pellet-containing tablets (GPCT). GPCT and traditional pellet-containing tablets (PCT) were prepared according to 29 formulations devised by the Design Expert 7.0, with doxycycline ...
Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Artificial intelligence (AI) offers new possibilities for hit and lead finding in medicinal chemistry. Several instances of AI have been used for prospective de novo drug design. Among these, chemical language models have been shown to perform well i...
The advent of large-scale biomedical data and computational algorithms provides new opportunities for drug repurposing and discovery. It is of great interest to find an appropriate data representation and modeling method to facilitate these studies. ...
Accurate predictions of druggability and bioactivities of compounds are desirable to reduce the high cost and time of drug discovery. After more than five decades of continuing developments, quantitative structure-activity relationship (QSAR) methods...