Results 121 to 130 of about 943,135 (348)

Network-principled deep generative models for designing drug combinations as graph sets [PDF]

arXiv, 2020
Combination therapy has shown to improve therapeutic efficacy while reducing side effects. Importantly, it has become an indispensable strategy to overcome resistance in antibiotics, anti-microbials, and anti-cancer drugs. Facing enormous chemical space and unclear design principles for small-molecule combinations, the computational drug-combination ...
arxiv  

Integrative systems‐level analysis reveals a contextual crosstalk between hypoxia and global metabolism in human breast tumors

Molecular Oncology, EarlyView.
Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam, Salem Chouaib, Mohammad Askandar Iqbal   +2 more
wiley   +1 more source

Graphic Mining of High-Order Drug Interactions and Their Directional Effects on Myopathy Using Electronic Medical Records [PDF]

, 2015
We propose to study a novel pharmacovigilance problem for mining directional effects of high-order drug interactions on an adverse drug event (ADE). Our goal is to estimate each individual risk of adding a new drug to an existing drug combination.
Chakraborty, A., Cheng, L., Chiang, C.-W., Du, L., Li, L., Quinney, S.K., Shen, L., Wu, H., Zhang, P.   +8 more
core   +1 more source

BERTChem-DDI : Improved Drug-Drug Interaction Prediction from text using Chemical Structure Information [PDF]

arXiv, 2020
Traditional biomedical version of embeddings obtained from pre-trained language models have recently shown state-of-the-art results for relation extraction (RE) tasks in the medical domain. In this paper, we explore how to incorporate domain knowledge, available in the form of molecular structure of drugs, for predicting Drug-Drug Interaction from ...
arxiv  

Crosstalk between gut microbiota and tumor: tumors could cause gut dysbiosis and metabolic imbalance

Molecular Oncology, EarlyView.
In this research, we analyzed the relationship between gut microbiota and tumor. We discovered that both subcutaneous and metastatic tumors would alter the composition and metabolic function of gut microbiota. Meanwhile, fecal microbiota transplantation also indicated the anti‐tumor role of the gut microbiota, revealing the crosstalk between tumor and ...
Siyuan Zhang, Haimei Wen, Ying Chen, Jingya Ning, Di Hu, Yujiao Dong, Chenyu Yao, Bo Yuan, Shuanying Yang   +8 more
wiley   +1 more source

Natural product based anticancer drug combination discovery assisted by deep learning and network analysis

Frontiers in Natural Products
Drug combination therapies have shown effective performance in treating cancer through increased efficacy and circumvention of drug resistance through synergy.
Elton L. Cao
doaj   +1 more source

Prediction of drug combinations by integrating molecular and pharmacological data.

PLoS Computational Biology, 2011
Combinatorial therapy is a promising strategy for combating complex disorders due to improved efficacy and reduced side effects. However, screening new drug combinations exhaustively is impractical considering all possible combinations between drugs ...
Xing-Ming Zhao, Murat Iskar, Murat Iskar, Georg Zeller, Michael Kuhn, Vera van Noort, Peer Bork   +6 more
doaj   +1 more source

Deep graph embedding for prioritizing synergistic anticancer drug combinations [PDF]

arXiv, 2019
Drug combinations are frequently used for the treatment of cancer patients in order to increase efficacy, decrease adverse side effects, or overcome drug resistance. Given the enormous number of drug combinations, it is cost- and time-consuming to screen all possible drug pairs experimentally.
arxiv  

Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models [PDF]

arXiv, 2020
Drug combinations play an important role in therapeutics due to its better efficacy and reduced toxicity. Recent approaches have applied machine learning to identify synergistic combinations for cancer, but they are not applicable to new diseases with limited combination data. Given that drug synergy is closely tied to biological targets, we propose a \
arxiv  

Inhibition of acyl‐CoA synthetase long‐chain isozymes decreases multiple myeloma cell proliferation and causes mitochondrial dysfunction

Molecular Oncology, EarlyView.
Triacsin C inhibition of the acyl‐CoA synthetase long chain (ACSL) family decreases multiple myeloma cell survival, proliferation, mitochondrial respiration, and membrane potential. Made with Biorender.com. Multiple myeloma (MM) is an incurable cancer of plasma cells with a 5‐year survival rate of 59%.
Connor S. Murphy, Heather Fairfield, Victoria E. DeMambro, Samaa Fadel, Carlos A. Gartner, Michelle Karam, Christian Potts, Princess Rodriguez, Ya‐Wei Qiang, Habib Hamidi, Xiangnan Guan, Calvin P. H. Vary, Michaela R. Reagan   +12 more
wiley   +1 more source