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Using Machine Learning to Collect and Facilitate Remote Access to Biomedical Databases: Development of the Biomedical Database Inventory
(J M I R Publications, Inc., 2021-02-25)
[Abstract]
Background:
Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases.
Objective:
To address this issue, ...
A review on machine learning approaches and trends in drug discovery
(Research Network of Computational and Structural Biotechnology, 2021)
Abstract: Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science ...
Machine Learning in Management of Precautionary Closures Caused by Lipophilic Biotoxins
(Elsevier, 2022)
[Abstract] Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galicia, the Spanish main producer ...
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy
(BMC, 2024-03-07)
[Absctract]: For understanding a chemical compound’s mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed ...
Integrative Multi-Omics Data-Driven Approach for Metastasis Prediction in Cancer
(ACM, 2018)
[Abstract]
Nowadays biomedical research is generating huge amounts of omic data, covering all levels of genetic information from nucleotide sequencing to protein metabolism. In the beginning, data were analyzed independently ...
Artificial intelligence in paediatrics: Current events and challenges
(Elsevier, 2024-03)
[Abstract]: This article examines the use of artificial intelligence (AI) in the field of paediatric care within the framework of the 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral ...
Machine learning analysis of TCGA cancer data
(PeerJ Inc., 2021)
[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas ...
Molecular Docking and Machine Learning Analysis of Abemaciclib in Colon Cancer
(BioMed Central Ltd., 2020-07-08)
[Abstract]
Background -
The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is ...
Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection
(Nature, 2018-10-24)
[Abstract] Screening and in silico modeling are critical activities for the reduction of experimental costs. They also speed up research notably and strengthen the theoretical framework, thus allowing researchers to ...
A Novel Protocol Using Captive Portals for FIDO2 Network Authentication
(MDPI, 2024)
[Abstract]: FIDO2 authentication is starting to be applied in numerous web authentication services, aiming to replace passwords and their known vulnerabilities. However, this new authentication method has not been integrated ...