Machine learning and its applications for protozoal pathogens and protozoal infectious diseases

RS Hu, AEL Hesham, Q Zou - Frontiers in Cellular and Infection …, 2022 - frontiersin.org
In recent years, massive attention has been attracted to the development and application of
machine learning (ML) in the field of infectious diseases, not only serving as a catalyst for …

A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts

J Pan, Z Zhang, Y Li, J Yu, Z You, C Li… - Briefings in …, 2024 - academic.oup.com
Predicting interactions between microbes and hosts plays critical roles in microbiome
population genetics and microbial ecology and evolution. How to systematically characterize …

[HTML][HTML] Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging

CF Otesteanu, R Caldelari, V Heussler… - Computational and …, 2024 - Elsevier
Malaria, a significant global health challenge, is caused by Plasmodium parasites. The
Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study …

[HTML][HTML] Multi-level biological network analysis and drug repurposing based on leukocyte transcriptomics in severe COVID-19: in silico systems biology to precision …

P Sagulkoo, H Chuntakaruk, T Rungrotmongkol… - Journal of personalized …, 2022 - mdpi.com
The coronavirus disease 2019 (COVID-19) pandemic causes many morbidity and mortality
cases. Despite several developed vaccines and antiviral therapies, some patients …

[HTML][HTML] Gene association classification for autism spectrum disorder: Leveraging gene embedding and differential gene expression profiles to identify disease-related …

A Suratanee, K Plaimas - Applied Sciences, 2023 - mdpi.com
Identifying genes associated with autism spectrum disorder (ASD) is crucial for
understanding the underlying mechanisms of the disorder. However, ASD is a complex …

Heterogeneous network propagation with forward similarity integration to enhance drug–target association prediction

P Tangmanussukum, T Kawichai, A Suratanee… - PeerJ Computer …, 2022 - peerj.com
Identification of drug–target interaction (DTI) is a crucial step to reduce time and cost in the
drug discovery and development process. Since various biological data are publicly …

Phenolic content discrimination in Thai holy basil using hyperspectral data analysis and machine learning techniques

A Suratanee, P Chutimanukul, T Saelao… - Plos one, 2024 - journals.plos.org
Hyperspectral imaging has emerged as a powerful tool for the non-destructive assessment
of plant properties, including the quantification of phytochemical contents. Traditional …

Integration of various protein similarities using random forest technique to infer augmented drug-protein matrix for enhancing drug-disease association prediction

S Kitsiranuwat, A Suratanee, K Plaimas - Science Progress, 2022 - journals.sagepub.com
Identifying new therapeutic indications for existing drugs is a major challenge in drug
repositioning. Most computational drug repositioning methods focus on known targets …

[HTML][HTML] Immune-related protein interaction network in severe COVID-19 patients toward the identification of key proteins and drug repurposing

P Sagulkoo, A Suratanee, K Plaimas - Biomolecules, 2022 - mdpi.com
Coronavirus disease 2019 (COVID-19) is still an active global public health issue. Although
vaccines and therapeutic options are available, some patients experience severe conditions …

Current Trend and Performance Evaluation of Machine Learning Methods for Predicting Host-Pathogen Protein-Protein Interactions

J Emmanuel, I Isewon, G Olasehinde… - … and Business for …, 2024 - ieeexplore.ieee.org
Host-pathogen interactions (HPI) play a vital role in the study of infectious disease
mechanisms. Experimental identification of the interaction between a host and pathogen has …