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Binary Classification of Aqueous Solubility Using Support Vector Machines with Reduction and Recombination Feature Selection

Tiejun Cheng, Qingliang Li, Yanli Wang, Stephen H. Bryant
2011 Journal of Chemical Information and Modeling  
Our model was optimized in combination with a reduction and recombination feature selection strategy.  ...  In this work, we present a support vector machines model for the binary classification of solubility by taking advantage of the largest known public data set that contains over 46 000 compounds with experimental  ...  ' CONCLUSIONS In this study, we have presented a binary classification model of aqueous solubility using the SVM.  ... 
doi:10.1021/ci100364a pmid:21214224 pmcid:PMC3047290 fatcat:lgmqvfav3jbsniaqwbr5homxbq

Combining machine learning and high-throughput experimentation to discover photocatalytically active organic molecules

Xiaobo Li, Phillip M. Maffettone, Yu Che, Tao Liu, Linjiang Chen, Andrew Cooper
2021 Chemical Science  
Light-absorbing organic molecules are useful components in photocatalysts, but it is difficult to formulate reliable structure-property design rules.  ...  Acknowledgements The authors acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC) (EP/N004884/1), and the Leverhulme Trust via the Leverhulme Research Centre for  ...  Another consideration is solubility: while the molecules selected have, on the whole, low aqueous solubilities, some molecules in the library might have finite solubility in the water / TEA / MEOH mixture  ... 
doi:10.1039/d1sc02150h pmid:34476057 pmcid:PMC8372320 fatcat:52n5gpyzdbfytnmobavyrcefoy

Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases

David A. Winkler
2021 Frontiers in Chemistry  
The pathways for the development of machine learning methods in the short to medium term and the use of other artificial intelligence methods for drug discovery is discussed.  ...  Here, the application of artificial intelligence, largely the subset called machine learning, to modelling and prediction of biological activities and discovery of new drugs for neglected tropical diseases  ...  This study is again consistent with previous studies of training and testing with multiple data sets that show little difference between support vector machine and deep neural networks models trained on  ... 
doi:10.3389/fchem.2021.614073 pmid:33791277 pmcid:PMC8005575 fatcat:obk5rdcpb5eblmghmey63ulztm

Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery

Benjamin P. Brown, Oanh Vu, Alexander R. Geanes, Sandeepkumar Kothiwale, Mariusz Butkiewicz, Edward W. Lowe, Ralf Mueller, Richard Pape, Jeffrey Mendenhall, Jens Meiler
2022 Frontiers in Pharmacology  
In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design.  ...  We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines  ...  The neuron j, with associated weight vector w, with the lowest distance d to the randomly selected input vector x is the winner.  ... 
doi:10.3389/fphar.2022.833099 pmid:35264967 pmcid:PMC8899505 fatcat:l5dpfgmkezgybd7qx6xjqxittq

Pattern Recognition and Pathway Analysis with Genetic Algorithms in Mass Spectrometry Based Metabolomics

Wei Zou, Vladimir Tolstikov
2009 Algorithms  
It was found that small groups of potential top predictors selected with PCA-DA and GA are different and unique. Annotated GC-TOF-MS data generated identified feature metabolites.  ...  Unsupervised methods, such as principle component analysis (PCA) and clustering, and supervised methods, such as classification and PCA-DA (discriminatory analysis) were used for data mining.  ...  We are grateful to Professor David Neale from Department of Plant Sciences and Professor Robert Weiss from Department of Internal Medicine of UC Davis for providing samples and corresponding descriptive  ... 
doi:10.3390/a2020638 fatcat:s3dqmtdtovdalmo6n2qqmzacr4

Fragment Graphical Variational AutoEncoding for Screening Molecules with Small Data [article]

John Armitage, Leszek J. Spalek, Malgorzata Nguyen, Mark Nikolka, Ian E. Jacobs, Lorena Marañón, Iyad Nasrallah, Guillaume Schweicher, Ivan Dimov, Dimitrios Simatos, Iain McCulloch, Christian B. Nielsen (+2 others)
2019 arXiv   pre-print
In the majority of molecular optimization tasks, predictive machine learning (ML) models are limited due to the unavailability and cost of generating big experimental datasets on the specific task.  ...  These approaches produce a set of candidate molecules which have to be ranked using limited experimental data or expert knowledge.  ...  The specific basis vectors used in each model was determined in situ by ranking the Pearson coefficient of each basis vector and selecting the top number of vectors with the largest Pearson coefficient  ... 
arXiv:1910.13325v2 fatcat:ecc2u6xkqjaw3j43hawgbr373u

A subcellular atlas of Toxoplasma reveals the functional context of the proteome [article]

Konstantin Barylyuk, Ludek Koreny, Huiling Ke, Simon Butterworth, Oliver M Crook, Imen Lassadi, Vipul Gupta, Eelco C Tromer, Tobias Mourier, Tim J Stevens, Lisa M Breckels, Arnab Pain (+2 others)
2020 bioRxiv   pre-print
The evolution of unique apicomplexan cellular compartments is concomitant with vast proteomic novelty that defines these new cell organizations and their functions.  ...  These adaptations drive their recognition and non-destructive penetration of host′s cells and the elaborate reengineering of these cells to promote growth, dissemination, and the countering of host defenses  ...  Superior, No1.5H with a thickness of 170 μm ± 5 μm) were used in cell culture and Vectashield (Vector Laboratories) was used as mounting reagent.  ... 
doi:10.1101/2020.04.23.057125 fatcat:posfb3csqbakxpr5l5m5i672vq

Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation [article]

Joshua K Peeples, Julie F Jameson, Nisha M Kotta, Jonathan M Grasman, Whitney L Stoppel, Alina Zare
2021 bioRxiv   pre-print
Methods: We used CNN models with novel spatial histogram layer(s) that can more accurately identify and segment regions of adipose tissue in hematoxylin and eosin (H&E) and Masson's Trichrome stained images  ...  models with a supplemental "attention"-inspired mechanism (JOSHUA+ and UNET+).  ...  Acknowledgments The Stoppel Lab thanks the undergraduate students that helped with silk solution preparation and the initial startup of the lab at UF and the undergraduate students that started the initial  ... 
doi:10.1101/2021.11.22.469463 fatcat:fxpmd7qrubaefea54hemzvhfi4


Gajalakshmi Dr. P.
2020 International Journal of Pharma and Bio Sciences  
The aqueous RNA phase was then transferred to a clean tube and then added 500 µl of Iso propanol / 1 ml of Tri reagent and vortexed for 5 min.  ...  . 8 P53 expression analysis (PCR) P53 gene amplification was performed in Eppendorf E331 PCR machine using the following typespecific PCR primers for the p53 gene with Forward sequence: CCTCAGCATCTTATCCGAGTGG  ...  Joseph College (Autonomous), Trichy, India for identifying and authenticating the plant materials used in this investigation.  ... 
doi:10.22376/ijpbs/ijlpr/sp07/jan/2020.1-87 fatcat:6lb7xdovbre7zle2hi7fx2erde

Recent Development and Application of Virtual Screening in Drug Discovery: An Overview

Tingjun Hou, Xiaojie Xu
2004 Current pharmaceutical design  
Here, the basic ideas and computational tools for virtual screening have been briefly introduced, and emphasis is placed on aspects of recent development of docking-based virtual screening, scoring functions  ...  Virtual screening, especially the structure-based virtual screening, has emerged as a reliable, cost-effective and time-saving technique for the discovery of lead compounds.  ...  ACKNOWLEDGEMENTS This project is supported by National Natural Science Foundation of China (NSFC 29992590-2).  ... 
doi:10.2174/1381612043452721 pmid:15078130 fatcat:ypsj2fqvhna7lm6fjbaqvxccvu

Recent Development and Application of Virtual Screening in Drug Discovery: An Overview [chapter]

Tingjun Hou, Xiaojie Xu
2012 Frontiers in Medicinal Chemistry - (Volume 3)  
Here, the basic ideas and computational tools for virtual screening have been briefly introduced, and emphasis is placed on aspects of recent development of docking-based virtual screening, scoring functions  ...  Virtual screening, especially the structure-based virtual screening, has emerged as a reliable, cost-effective and time-saving technique for the discovery of lead compounds.  ...  ACKNOWLEDGEMENTS This project is supported by National Natural Science Foundation of China (NSFC 29992590-2).  ... 
doi:10.2174/978160805206610603010675 fatcat:a5vspahtpremdkmcouneiw6isi

The 18th European Symposium on Quantitative Structure–Activity Relationships

Anna Tsantili-Kakoulidou, Dimitris K Agrafiotis
2011 Expert Opinion on Drug Discovery  
especially its positioning into the ATP binding cleft. 4 CDK1 inhibitory potency or/and selectivity improvement efforts led to the synthesis of new selectively substituted pyrrolo [2,3-a]carbazoles.  ...  Wigley for the contribution to this work with the x-ray structure of the protein ligand to the GR1222222.  ...  Several QSAR modeling approaches including k-nearest neighbors (kNN), support vector machines (SVM), RBF Neural Networks, least squares support vector machines (LS-SVM) were combined with a pool of 2D  ... 
doi:10.1517/17460441.2011.560604 pmid:22646021 fatcat:tb4bhvtnpzahxm4xba7iw4afuy

Agricultural Potentials of Molecular Spectroscopy and Advances for Food Authentication: An Overview

John-Lewis Zinia Zaukuu, Eszter Benes, György Bázár, Zoltán Kovács, Marietta Fodor
2022 Processes  
This review aims to provide a detailed overview of common molecular spectroscopic techniques and their use for agricultural and food quality management.  ...  and discussed to highlight new trends, accomplishments, challenges, and benefits of using molecular spectroscopic methods for studying food matrices.  ...  Acknowledgments: We are grateful for the support of Doctoral School of Food Science of the Hungarian University of Agricultural and Life Sciences.  ... 
doi:10.3390/pr10020214 fatcat:fkjoyec7t5ds7nzdk6mx5b64na

High‐Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research

Anass Benayad, Diddo Diddens, Andreas Heuer, Anand Narayanan Krishnamoorthy, Moumita Maiti, Frédéric Le Cras, Maxime Legallais, Fuzhan Rahmanian, Yuyoung Shin, Helge Stein, Martin Winter, Christian Wölke (+2 others)
2021 Advanced Energy Materials  
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not.  ...  The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.  ...  (BIG-MAP) and 957213 (BATTERY2030PLUS) as well as Thilo Klüppel for the illustrations used in Figures 2, 4 Open access funding enabled and organized by Projekt DEAL.  ... 
doi:10.1002/aenm.202102678 fatcat:cwqm236k7jedpd4ydywpdgl5om

Design, Screening, and Testing of Non-Rational Peptide Libraries with Antimicrobial Activity: In Silico and Experimental Approaches

Paola Ruiz Puentes, María C. Henao, Carlos E. Torres, Saúl C. Gómez, Laura A. Gómez, Juan C. Burgos, Pablo Arbeláez, Johann F. Osma, Carolina Muñoz-Camargo, Luis H. Reyes, Juan C. Cruz
2020 Antibiotics  
We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units.  ...  Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries.  ...  Additionally, support from the Chemical Engineering Program at UniCartagena is gratefully acknowledged. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/antibiotics9120854 pmid:33265897 fatcat:2r4x6gjb4ffmncbozfutzbp5dm
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