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ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery

Christian Partl, Alexander Lex, Marc Streit, Hendrik Strobelt, Anne-Mai Wassermann, Hanspeter Pfister, Dieter Schmalstieg
2014 IEEE Transactions on Visualization and Computer Graphics  
Index Terms-Multi-relational data, visual data analysis, drug discovery • Christian Partl and Dieter Schmalstieg are with Graz University of Technology.  ...  To remedy this, we developed ConTour, an interactive visual analytics technique that enables the exploration of these complex, multi-relational datasets.  ...  ACKNOWLEDGMENTS The authors wish to thank Felix Reisen, Mark Borowsky, and the anonymous reviewers for their valuable input and feedback.  ... 
doi:10.1109/tvcg.2014.2346752 pmid:26356902 pmcid:PMC4720990 fatcat:lxaaqphkzne3zohxcupmy7lw6m

A Cell Derived Active Contour (CDAC) Method for Robust Tracking in Low Frame Rate, Low Contrast Phase Microscopy - an Example: The Human hNT Astrocyte

Alireza Nejati Javaremi, Charles P. Unsworth, E. Scott Graham, Irene Georgakoudi
2013 PLoS ONE  
This Cell-Derived Active Contour (CDAC) method is compared with two state-of-the-art segmentation methods for phasecontrast microscopy.  ...  We demonstrate quantitatively better results for CDAC as compared to similar segmentation methods, and we also demonstrate the reliable segmentation of qualitatively different data sets that were not possible  ...  Acknowledgements We would like to thank Ivo Sbalzarini for kindly providing us with sample code and data as well as advising us on the proper parameters to use for the Ambühl algorithm on our data sets  ... 
doi:10.1371/journal.pone.0082883 pmid:24358233 pmcid:PMC3866173 fatcat:uh45wjjj5jbrxcadofkdviqxzu

Data-driven modeling and learning in science and engineering

Francisco J. Montáns, Francisco Chinesta, Rafael Gómez-Bombarelli, J. Nathan Kutz
2019 Comptes rendus. Mecanique  
Data-driven modeling and scientific discovery is a change of paradigm on how many problems, both in science and engineering, are addressed.  ...  In this paper we review the application of data-driven modeling and model learning procedures to different fields in science and engineering.  ...  JNK acknowledges support from the Air Force Office of Scientific Research (AFOSR) grant FA9550-17-1-0329.  ... 
doi:10.1016/j.crme.2019.11.009 fatcat:7rtlth7ncreqthugtduxtzjpky

2014 Index IEEE Transactions on Visualization and Computer Graphics Vol. 20

2015 IEEE Transactions on Visualization and Computer Graphics  
., +, TVCG Dec. 2014 2388-2396 Drugs ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery.  ...  ., +, TVCG Dec. 2014 2033-2042 ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery.  ... 
doi:10.1109/tvcg.2014.2368193 fatcat:nm3sijdvbza5nmxyina4rqinnu

Artificial intelligence in healthcare: transforming the practice of medicine

Junaid Bajwa, Usman Munir, Aditya Nori, Bryan Williams
2021 Future healthcare journal  
Artificial intelligence (AI) is a powerful and disruptive area of computer science, with the potential to fundamentally transform the practice of medicine and the delivery of healthcare.  ...  of AI augmented healthcare systems.  ...  AI-driven drug discovery AI will drive significant improvement in clinical trial design and optimisation of drug manufacturing processes, and, in general, any combinatorial optimisation process in healthcare  ... 
doi:10.7861/fhj.2021-0095 pmid:34286183 pmcid:PMC8285156 fatcat:nja3ltjvazak5gfhmvvbr5fbhm

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities

Marilia N. N. Lima, Cleber C. Melo-Filho, Gustavo C. Cassiano, Bruno J. Neves, Vinicius M. Alves, Rodolpho C. Braga, Pedro V. L. Cravo, Eugene N. Muratov, Juliana Calit, Daniel Y. Bargieri, Fabio T. M. Costa, Carolina H. Andrade
2018 Frontiers in Pharmacology  
Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds.  ...  an attractive antimalarial drug target.  ...  The authors would like to thank Brazilian funding agencies, CNPq, FAPEG, FAPESP, and CAPES for financial support and fellowships.  ... 
doi:10.3389/fphar.2018.00146 pmid:29559909 pmcid:PMC5845645 fatcat:d7nxhlcaabc25mijazt7ld4aqa

An Application Review of Artificial Intelligence in Prevention and Cure of COVID-19 Pandemic

Peipeng Yu, Zhihua Xia, Jianwei Fei, Sunil Kumar Jha
2020 Computers Materials & Continua  
Due to excellent learning ability, AI has played an important role in drug development, epidemic forecast, and clinical diagnosis.  ...  As a powerful tool, artificial intelligence (AI) has been successfully applied to solve various complex problems ranging from big data analysis to computer vision.  ...  Acknowledgement: Thanks Zhentian Zhang and Wenhao Zhou for his help in completing this article. The author is also very grateful to the reviewers.  ... 
doi:10.32604/cmc.2020.011391 fatcat:h3ibltvmjzbkplwqkbggksiq2i

Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies

Nicholas M. Pearce, Rachael Skyner, Tobias Krojer
2022 Frontiers in Molecular Biosciences  
datasets per day.  ...  Crystal structures of target proteins in complex with small-molecule ligands are of immense importance for structure-based drug design (SBDD) and their rapid turnover is a prerequisite for accelerated  ...  The large-scale availability of related crystallographic datasets from fragment screening experiments enabled the development of a data-driven multi-dataset ligand identification method: PanDDA (Pearce  ... 
doi:10.3389/fmolb.2022.861491 pmid:35480897 pmcid:PMC9035521 fatcat:l6fpnkmppbaxpdmiury2qr2fiy

Graph Neural Networks and Their Current Applications in Bioinformatics

Xiao-Meng Zhang, Li Liang, Lin Liu, Ming-Jing Tang
2021 Frontiers in Genetics  
Meanwhile, according to the specific applications for various omics data, we categorize and discuss the related studies in three aspects: disease prediction, drug discovery, and biomedical imaging.  ...  With the rapid accumulation of biological network data, GNNs have also become an important tool in bioinformatics.  ...  X-MZ contributed to the investigation and data curation. All authors have read and agreed to the published version of the manuscript.  ... 
doi:10.3389/fgene.2021.690049 fatcat:4p55ap6sivcy7h6dpne5fut6lu

Visualization of confocal microscopic biomolecular data

Zhanping Liu, Robert J. Moorhead II, Robert L. Galloway, Jr., Kevin R. Cleary
2005 Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display  
This paper presents major challenges in visualizing confocal microscopic biomolecular data, followed by a survey of related work.  ...  intuitive comprehension of the data.  ...  exploration of scientific data.  ... 
doi:10.1117/12.593652 dblp:conf/miigp/LiuM05 fatcat:tkas2j55afdh5fntdenchffmue

Evolutionary Computation and QSAR Research

Vanessa Aguiar-Pulido, Marcos Gestal, Maykel Cruz-Monteagudo, Juan Rabunal, Julian Dorado, Cristian Munteanu
2013 Current Computer - Aided Drug Design  
The successful high throughput screening of molecule libraries for a specific biological property is one of the main improvements in drug discovery.  ...  Thus, this review explains the basic of the genetic algorithms and genetic programming as evolutionary computation approaches, the selection methods for highdimensional data in QSAR, the methods to build  ...  Therefore, it could be said that current drug design is data-driven and the most important objective is to discover knowledge from raw data.  ... 
doi:10.2174/1573409911309020006 pmid:23700999 fatcat:zsipotcovzhlhg7wrgjfkc5wvu

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal [article]

J. Michael Krill-Burger, Joshua M. Dempster, Ashir A. Borah, Brenton R. Paolella, David E. Root, Todd R. Golub, Jesse S. Boehm, William C. Hahn, James M. McFarland, Francisca Vazquez, Aviad Tsherniak
2022 bioRxiv   pre-print
for a wider range of gene targets than could be detected using either dataset alone.  ...  Here, we use CRISPR-Cas9 and RNAi screening data for more than 400 shared cell lines to represent knockout and partial suppression genetic perturbation modalities and evaluate the utility of each for therapeutic  ...  The funders did not influence the conception, design, or analysis of the study or the writing of this manuscript.  ... 
doi:10.1101/2022.03.02.482624 fatcat:p6ia5wahbndvdmuwintslniife

Visualizing the drug target landscape

Stephen J. Campbell, Anna Gaulton, Jason Marshall, Dmitri Bichko, Sid Martin, Cory Brouwer, Lee Harland
2010 Drug Discovery Today  
A retrospective on how the application of data integration and visualisation has been used to connect disparate information sources into a drug-discovery focused, decision making environment.  ...  Acknowledgements The authors acknowledge the guidance of Enoch Huang and substantial input from Robert Hernandez, Markella Skempri, Dave  ...  Information maps Cartographic techniques have also shown great value in representing large, multi-factorial datasets such as gene expression arrays and other life science data.  ... 
doi:10.1016/j.drudis.2009.09.011 pmid:19840866 fatcat:csd4hsaokjgbjjbq4azwdnf24q

Exposing Hidden Alternative Backbone Conformations in X-ray Crystallography Using qFit

Daniel A. Keedy, James S. Fraser, Henry van den Bedem, Amarda Shehu
2015 PLoS Computational Biology  
For example, we discover glycine-driven peptide flips in the inhibitor-gating "flaps" of the drug target HIV protease that were not modeled in the original structures.  ...  Automatically modeling "hidden" multiple conformations of proteins using our algorithm may help drive biomedically relevant insights in structural biology pertaining to, e.g., drug discovery for HIV-1  ...  Such data-driven computational approaches to studying the dynamic relationship between protein structure and function will be especially powerful when applied to series of datasets in which the protein  ... 
doi:10.1371/journal.pcbi.1004507 pmid:26506617 pmcid:PMC4624436 fatcat:yaj7baxibnenzbvxi2l2b73iby

Visualizing the drug target landscape

Stephen J. Campbell, Anna Gaulton, Jason Marshall, Dmitri Bichko, Sid Martin, Cory Brouwer, Lee Harland
2012 Drug Discovery Today  
A retrospective on how the application of data integration and visualisation has been used to connect disparate information sources into a drug-discovery focused, decision making environment.  ...  Acknowledgements The authors acknowledge the guidance of Enoch Huang and substantial input from Robert Hernandez, Markella Skempri, Dave  ...  Information maps Cartographic techniques have also shown great value in representing large, multi-factorial datasets such as gene expression arrays and other life science data.  ... 
doi:10.1016/j.drudis.2011.12.005 pmid:22178891 fatcat:qvdkemacwbaibb42sb4om6dxke
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