Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
Discovery and development of biopeptides are time‐consuming, laborious, and dependent
on various factors. Data‐driven computational methods, especially machine learning (ML) …
on various factors. Data‐driven computational methods, especially machine learning (ML) …
Machine learning methods, databases and tools for drug combination prediction
L Wu, Y Wen, D Leng, Q Zhang, C Dai… - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious efficacy on complex diseases and can greatly
reduce the development of drug resistance. However, even with high-throughput screens …
reduce the development of drug resistance. However, even with high-throughput screens …
MRMD2. 0: a python tool for machine learning with feature ranking and reduction
S He, F Guo, Q Zou - Current Bioinformatics, 2020 - ingentaconnect.com
Aims: The study aims to find a way to reduce the dimensionality of the dataset. Background:
Dimensionality reduction is the key issue of the machine learning process. It does not only …
Dimensionality reduction is the key issue of the machine learning process. It does not only …
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Abstract N6-methyladenosine (m 6 A) is a prevalent methylation modification and plays a
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
M6APred-EL: a sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning
L Wei, H Chen, R Su - Molecular Therapy-Nucleic Acids, 2018 - cell.com
N6-methyladenosine (m 6 A) modification is the most abundant RNA methylation
modification and involves various biological processes, such as RNA splicing and …
modification and involves various biological processes, such as RNA splicing and …
PVP-SVM: sequence-based prediction of phage virion proteins using a support vector machine
Accurately identifying bacteriophage virion proteins from uncharacterized sequences is
important to understand interactions between the phage and its host bacteria in order to …
important to understand interactions between the phage and its host bacteria in order to …
Develo** a multi-dose computational model for drug-induced hepatotoxicity prediction based on toxicogenomics data
Drug-induced hepatotoxicity may cause acute and chronic liver disease, leading to great
concern for patient safety. It is also one of the main reasons for drug withdrawal from the …
concern for patient safety. It is also one of the main reasons for drug withdrawal from the …
A robust method for safety evaluation of steel trusses using Gradient Tree Boosting algorithm
In this study, an efficient method is proposed for the safety evaluation of steel trusses using
the gradient tree boosting (GTB) algorithm, one of the most powerful techniques in machine …
the gradient tree boosting (GTB) algorithm, one of the most powerful techniques in machine …
iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space
Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries.
Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive …
Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive …
PredT4SE-stack: prediction of bacterial type IV secreted effectors from protein sequences using a stacked ensemble method
Gram-negative bacteria use various secretion systems to deliver their secreted effectors.
Among them, type IV secretion system exists widely in a variety of bacterial species, and …
Among them, type IV secretion system exists widely in a variety of bacterial species, and …