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Deep learning for molecular generation and optimization - a review of the state of the art [article]

Daniel C. Elton, Zois Boukouvalas, Mark D. Fuge, Peter W. Chung
2019 arXiv   pre-print
Inspired by these successes, researchers are now applying deep generative modeling techniques to the generation and optimization of molecules - in our review we found 45 papers on the subject published  ...  grammars and 3D representations, the importance of reward function design, the need for better standards for benchmarking and testing, and the benefits of adversarial training and reinforcement learning  ...  William Wilson, and Dr. Andrey Gorlin for their input and for proofreading the manuscript.  ... 
arXiv:1903.04388v2 fatcat:gc3sn6oe3jea3htxywwsxf5q6m

Machine learning applications for COVID-19: A state-of-the-art review [article]

Firuz Kamalov, Aswani Cherukuri, Hana Sulieman, Fadi Thabtah, Akbar Hossain
2021 arXiv   pre-print
We cover four major areas of research: forecasting, medical diagnostics, drug development, and contact tracing. We review and analyze the most successful state of the art studies.  ...  The body of literature related to applications of machine learning and artificial intelligence to COVID-19 is constantly growing.  ...  Our goal is to provide a quick, but sufficiently detailed, overview of the current state of the art in machine learning research applied to COVID-19.  ... 
arXiv:2101.07824v1 fatcat:c4j7gxwhdndobd5x6yvqeehvny

Diagnosis of COVID-19 for controlling the pandemic: A review of the state-of-the-art

Nastaran Taleghani, Fariborz Taghipour
2020 Biosensors & bioelectronics  
Scientists and researchers are developing tests for the rapid detection of individuals who may carry the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), while striving to find a suitable  ...  Herein, we present recent technologies and techniques that have been implemented for the diagnosis of COVID-19.  ...  Acknowledgment The authors would like to acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC) for its financial support.  ... 
doi:10.1016/j.bios.2020.112830 pmid:33339696 pmcid:PMC7694563 fatcat:abe5nuobcjadfl2hsioqzgkgii

Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review

H. Swapnarekha, Himansu Sekhar Behera, Janmenjoy Nayak, Bighnaraj Naik
2020 Chaos, Solitons & Fractals  
In this paper, a state-of-the-art analysis of the ongoing machine learning (ML) and deep learning (DL) methods in the diagnosis and prediction of COVID-19 has been done.  ...  In this study, some factors such as type of methods(machine learning, deep learning, statistical & mathematical) and the impact of COVID research of the nature of data used for the forecasting and prediction  ...  The authors declare that this manuscript has no conflict of interest with any other published source and has not been published previously (partly or in full).  ... 
doi:10.1016/j.chaos.2020.109947 pmid:32836916 pmcid:PMC7256553 fatcat:uytoc2bfung7hhw47z2rnbiw5q

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

Elio Tuci, Muhanad H. M. Alkilabi, Otar Akanyeti
2018 Frontiers in Robotics and AI  
Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position  ...  In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs.  ...  In section 5, we provide an informative and constructive discussion on the state of the art of MRSs engaged in cooperative transport that helps to identify objectives for interesting future directions  ... 
doi:10.3389/frobt.2018.00059 pmid:33500940 pmcid:PMC7805628 fatcat:dvjxo6dzkzdspfhyu76ttrnbzq

Plasma Modeling and Prebiotic Chemistry: A Review of the State-of-the-Art and Perspectives

Gaia Micca Longo, Luca Vialetto, Paola Diomede, Savino Longo, Vincenzo Laporta
2021 Molecules  
We review the recent progress in the modeling of plasmas or ionized gases, with compositions compatible with that of primordial atmospheres.  ...  They are basic processes, for example, in the famous Miller-Urey experiment, and become relevant in any prebiotic scenario where the primordial atmosphere is significantly ionized by electrical activity  ...  Colonna (Università di Milano, Milano, Italy) for careful reading of the manuscript and discussions.  ... 
doi:10.3390/molecules26123663 fatcat:2tyzub54knf2ze4j3wadluuggm

Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – A state-of-the-art review

Yongliang (Harry) Yan, Tohid Borhani, Gokul Subraveti, Nagesh Pai, Vinay Prasad, Arvind Rajendran, Paula Nkulikiyinka, Jude Odianosen Asibor, Zhien Zhang, Ding Shao, Lijuan Wang, Wenbiao Zhang (+7 others)
2021 Energy & Environmental Science  
Carbon Capture Utilisation and Storage (CCUS) will play a critical role in future decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of climate change.  ...  Sun 231 employed a deep reinforcement learning method, namely the deep Q-learning (DQL) algorithm, to handle optimization of carbon storage reservoir management.  ...  Oliveira et al. 135 proposed a real-time soft sensor for a PSA unit based on deep learning networks.  ... 
doi:10.1039/d1ee02395k fatcat:oherbaerwfcarc744bn77pu77y

White matter tractography for neurosurgical planning: A topography-based review of the current state of the art

Walid I. Essayed, Fan Zhang, Prashin Unadkat, G. Rees Cosgrove, Alexandra J. Golby, Lauren J. O'Donnell
2017 NeuroImage: Clinical  
We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient  ...  We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications.  ...  Acknowledgements We gratefully acknowledge the funding provided by the following National Institutes of Health (NIH) grants: R25:114526, U01:CA199459, P41:EB015898, P41:EB015902.  ... 
doi:10.1016/j.nicl.2017.06.011 pmid:28664037 pmcid:PMC5480983 fatcat:zikpud4t6vg3dj37s3sl6ib2nm

Long Non-Coding RNAs in Diagnosis, Treatment, Prognosis, and Progression of Glioma: A State-of-the-Art Review

Sara Momtazmanesh, Nima Rezaei
2021 Frontiers in Oncology  
Notably, a profound understanding of the underlying molecular pathways involved in the function of lncRNAs is required to develop novel therapeutic targets.  ...  Despite considerable advances, the exact molecular pathways involved in tumor progression are not fully elucidated, and patients commonly face a poor prognosis.  ...  Applying artificial intelligence technology, including machine-learning and deep-learning models, can also aid in the identification of novel lncRNAs associated with a specific disease mainly via classification  ... 
doi:10.3389/fonc.2021.712786 fatcat:j2sucl73a5ad7kmnhfihxi4jhm

Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry

Najmeh Khalili-Mahani, Serge A.R.B. Rombouts, Matthias J.P. van Osch, Eugene P. Duff, Felix Carbonell, Lisa D. Nickerson, Lino Becerra, Albert Dahan, Alan C Evans, Jean-Paul Soucy, Richard Wise, Alex P. Zijdenbos (+1 others)
2017 Human Brain Mapping  
PhfMRI refers to a specific case of pharma-RSfMRI where a drug is the stimulus of interest and dynamics of drug dosage and uptake are used for estimation of a hemodynamic response. r Pharma-RSfMRI: Biomarkers  ...  This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain.  ...  Second, the community must adopt a set of standardized basic practices for data acquisition, which takes advantages of the state-of-the-art imaging technologies for acquiring multispectral and quantitative  ... 
doi:10.1002/hbm.23516 pmid:28145075 fatcat:o6h7ahdzerbbngzx6vcfsvbn3q

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Susanna Manrubia, José A. Cuesta, Jacobo Aguirre, Sebastian E. Ahnert, Lee Altenberg, Alejandro V. Cano, Pablo Catalán, Ramon Diaz-Uriarte, Santiago F. Elena, Juan Antonio García-Martín, Paulien Hogeweg, Bhavin S. Khatri (+6 others)
2021 Physics of Life Reviews  
We refer to this generally as the problem of the genotype-phenotype map.  ...  This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues  ...  In this review, we discuss the state-of-the-art of genotype-to-organism research and future research avenues in the field. The review is structured into four major parts.  ... 
doi:10.1016/j.plrev.2021.03.004 pmid:34088608 fatcat:kdgh5d2g2bgclcluvbp5jndm3q

State of the Art Review on Genetics and Precision Medicine in Arrhythmogenic Cardiomyopathy

Viraj Patel, Babken Asatryan, Bhurint Siripanthong, Patricia B. Munroe, Anjali Tiku-Owens, Luis R. Lopes, Mohammed Y. Khanji, Alexandros Protonotarios, Pasquale Santangeli, Daniele Muser, Francis E. Marchlinski, Peter A. Brady (+1 others)
2020 International Journal of Molecular Sciences  
This review details the genetic basis of ACM with specific genotype-phenotype associations, providing the reader with a nuanced perspective of this condition; whilst also proposing a future roadmap to  ...  Further to this, wider evaluation of family members has revealed incomplete penetrance and variable expressivity in ACM, suggesting a complex genotype-phenotype relationship.  ...  Precision clinical care requires an in-depth and nuanced understanding of the genetics of ACM, whilst also understanding the correlating deep phenotypic characteristics, to ensure optimal timely and targeted  ... 
doi:10.3390/ijms21186615 pmid:32927679 fatcat:yc3i42vfhzawne7tgrnqla774u

Paradigm Shift: The Promise of Deep Learning in Molecular Systems Engineering and Design

Abdulelah S. Alshehri, Fengqi You
2021 Frontiers in Chemical Engineering  
Just as the roles of instrumentation in the old chemical revolutions, we reinforce the necessity for integrating deep learning in molecular systems engineering and design as a transformative catalyst towards  ...  We further spotlight recent advances and promising directions for several deep learning architectures, methods, and optimization platforms.  ...  To envision the path forward, we distill relevant trends and advances in deep learning that have resulted in recent breakthroughs and state-of-the-art results with connections to molecular systems.  ... 
doi:10.3389/fceng.2021.700717 fatcat:sxsqy3ik3bf7bnzftxmlippvfy

Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design – Toward a Unified Approach: State-of-the-Art and Future Directions [article]

Abdulelah S. Alshehri, Rafiqul Gani, Fengqi You
2020 arXiv   pre-print
In view of the computational challenges plaguing knowledge-based methods and techniques, we survey the current state-of-the-art applications of deep learning to molecular design as a fertile approach towards  ...  The main focus of the survey is given to deep generative modeling of molecules under various deep learning architectures and different molecular representations.  ...  Section 3 surveys the current state-of-the-art in the nascent area of deep learning for molecular design, covering three main elements: molecular representations, major deep generative architectures, and  ... 
arXiv:2005.08968v2 fatcat:p2mfdbkqsjekxa6qwoz5xpfzuu

Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery

Changwon Suh, Clyde Fare, James A. Warren, Edward O. Pyzer-Knapp
2020 Annual review of materials research (Print)  
Here, we review the accomplishments to date of the community and assess the maturity of state-of-the-art, data-intensive research activities that combine perspectives from materials science and chemistry  ...  Expected final online publication date for the Annual Review of Materials Research, Volume 50 is July 1, 2020. Please see for revised estimates.  ...  The state of the art for representation of a molecular graph has moved to the use of deep learning, though there is still some research into nonneural methods such as the N-gram graph representation (  ... 
doi:10.1146/annurev-matsci-082019-105100 fatcat:dyxljg2mu5grzlakeeatvyymd4
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