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ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery
2014
IEEE Transactions on Visualization and Computer Graphics
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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
2013
PLoS ONE
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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
2019
Comptes rendus. Mecanique
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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
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., +, 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
2021
Future healthcare journal
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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
2018
Frontiers in Pharmacology
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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
2020
Computers Materials & Continua
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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
2022
Frontiers in Molecular Biosciences
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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
2021
Frontiers in Genetics
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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
2005
Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display
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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
2013
Current Computer - Aided Drug Design
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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]
2022
bioRxiv
pre-print
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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
2010
Drug Discovery Today
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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
2015
PLoS Computational Biology
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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
2012
Drug Discovery Today
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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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