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Amid the pandemic of 2019 novel coronavirus disease (COVID-19) infected by SARS-CoV-2, a vast amount of drug research for prevention and treatment has been quickly conducted, but these efforts have been unsuccessful thus far. Our objective…

Quantitative Methods · Quantitative Biology 2022-02-03 Kanglin Hsieh , Yinyin Wang , Luyao Chen , Zhongming Zhao , Sean Savitz , Xiaoqian Jiang , Jing Tang , Yejin Kim

The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses (HCoVs), which spreads rapidly around the world. Compared with new drug development, drug repurposing may be the best shortcut for treating COVID-19. Therefore, we…

Machine Learning · Computer Science 2021-07-21 Shuting Jin , Xiangxiang Zeng , Wei Huang , Feng Xia , Changzhi Jiang , Xiangrong Liu , Shaoliang Peng

To better understand the potential of drug repurposing in COVID-19, we analyzed control strategies over essential host factors for SARS-CoV-2 infection. We constructed comprehensive directed protein-protein interaction networks integrating…

There have been more than 850,000 confirmed cases and over 48,000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone.…

Quantitative Methods · Quantitative Biology 2020-05-25 Xiangxiang Zeng , Xiang Song , Tengfei Ma , Xiaoqin Pan , Yadi Zhou , Yuan Hou , Zheng Zhang , George Karypis , Feixiong Cheng

The 2019 novel coronavirus (SARS-CoV-2) pandemic has resulted in more than a million deaths, high morbidities, and economic distress worldwide. There is an urgent need to identify medications that would treat and prevent novel diseases like…

Machine Learning · Computer Science 2020-12-04 Siddhant Doshi , Sundeep Prabhakar Chepuri

In the past several months, COVID-19 has spread over the globe and caused severe damage to the people and the society. In the context of this severe situation, an effective drug discovery method to generate potential drugs is extremely…

Machine Learning · Computer Science 2021-04-26 Tianyue Cheng , Tianchi Fan , Landi Wang

The integration of machine learning methods into bioinformatics provides particular benefits in identifying how therapeutics effective in one context might have utility in an unknown clinical context or against a novel pathology. We aim to…

Machine Learning · Computer Science 2020-06-29 Semih Cantürk , Aman Singh , Patrick St-Amant , Jason Behrmann

Design of new drug compounds with target properties is a key area of research in generative modeling. We present a small drug molecule design pipeline based on graph-generative models and a comparison study of two state-of-the-art graph…

Machine Learning · Computer Science 2021-02-10 Logan Ward , Jenna A. Bilbrey , Sutanay Choudhury , Neeraj Kumar , Ganesh Sivaraman

Severe acute respiratory syndrome coronavirus two (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents an unprecedented global health challenge. Consequently, a large amount of research into…

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. It was first identified in Wuhan, China, and has since spread causing a global pandemic. Various studies have been performed to understand the…

Latent representations of drugs and their targets produced by contemporary graph autoencoder-based models have proved useful in predicting many types of node-pair interactions on large networks, including drug-drug, drug-target, and…

Biomolecules · Quantitative Biology 2022-11-01 Nhat Khang Ngo , Truong Son Hy , Risi Kondor

Currently, the number of patients with COVID-19 has significantly increased. Thus, there is an urgent need for developing treatments for COVID-19. Drug repurposing, which is the process of reusing already-approved drugs for new medical…

Quantitative Methods · Quantitative Biology 2020-08-13 Yonghyun Nam , Jae-Seung Yun , Seung Mi Lee , Ji Won Park , Ziqi Chen , Brian Lee , Anurag Verma , Xia Ning , Li Shen , Dokyoon Kim

Latent representations of drugs and their targets produced by contemporary graph autoencoder models have proved useful in predicting many types of node-pair interactions on large networks, including drug-drug, drug-target, and target-target…

Machine Learning · Computer Science 2023-02-20 Nhat Khang Ngo , Truong Son Hy , Risi Kondor

COVID-19 has created a global pandemic with high morbidity and mortality in 2020. Novel coronavirus (nCoV), also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), is responsible for this deadly disease. International…

Molecular Networks · Quantitative Biology 2020-05-11 Sovan Saha , Anup Kumar Halder , Soumyendu Sekhar Bandyopadhyay , Piyali Chatterjee , Mita Nasipuri , Subhadip Basu

The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. There are many therapeutics undergoing clinical trials, but there is no effective vaccine or therapy for…

Molecular Networks · Quantitative Biology 2020-07-01 Fuhai Li , Andrew P. Michelson , Randi Foraker , Ming Zhan , Philip R. O. Payne

Objective: To discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods. Methods: We propose a novel, integrative, and neural network-based literature-based discovery (LBD)…

Computation and Language · Computer Science 2021-02-10 Rui Zhang , Dimitar Hristovski , Dalton Schutte , Andrej Kastrin , Marcelo Fiszman , Halil Kilicoglu

Knowledge graph (KG) is used to represent data in terms of entities and structural relations between the entities. This representation can be used to solve complex problems such as recommendation systems and question answering. In this…

Artificial Intelligence · Computer Science 2022-12-09 Ajay Kumar Gogineni

The development of therapeutic targets for COVID-19 treatment is based on the understanding of the molecular mechanism of pathogenesis. The identification of genes and proteins involved in the infection mechanism is the key to shed out…

Biomolecules · Quantitative Biology 2021-05-19 Jayanta Kumar Das , Swarup Roy , Pietro Hiram Guzzi

Predicting interactions among heterogenous graph structured data has numerous applications such as knowledge graph completion, recommendation systems and drug discovery. Often times, the links to be predicted belong to rare types such as…

Machine Learning · Computer Science 2020-07-21 Vassilis N. Ioannidis , Da Zheng , George Karypis

Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19),…

Biomolecules · Quantitative Biology 2022-02-11 Xiaoqin Pan , Xuan Lin , Dongsheng Cao , Xiangxiang Zeng , Philip S. Yu , Lifang He , Ruth Nussinov , Feixiong Cheng
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