Machine Learning Approaches for Stem Cells

Mazalan, Mazlee; Do, Tien-Dung; Zaman, Wan Safwani Wan Kamarul; Ramlan, Effirul I.

doi:10.1007/s40778-023-00228-1

Cited by 3 publications

(1 citation statement)

References 81 publications

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“…Notably, machine learning is used in many fields, such as molecular biology and genomics, where it is essential for identifying complex relationships and patterns in genetic and molecular databases [8,12,13]. Various machine learning modes, such as supervised learning, semi-supervised learning, unsupervised learning, and reinforcement learning, are used, depending on the particular research goals and datasets, to drive groundbreaking discoveries and extract valuable insights in the field of genetics and in molecular research [14][15][16]. The literature has featured multiple research studies that highlight the synergy between machine learning and genetic data, especially in the context of EC [17,18] and PCOS [19,20].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches

Karadayı Ataş

2024

Mathematics

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Polycystic ovary syndrome (PCOS) and endometrial carcinoma (EC) are gynecological conditions that have attracted significant attention due to the higher prevalence of EC in patients with PCOS. Even with this proven association, little is known about the complex molecular pathways that connect PCOS to an increased risk of EC. In order to address this, our study presents two main innovations. To provide a solid basis for our analysis, we have first created a dataset of genes linked to EC and PCOS. Second, we start by building fixed-size ensembles, and then we refine the configuration of a single clustering algorithm within the ensemble at each step of the hyperparameter optimization process. This optimization evaluates the potential performance of the ensemble as a whole, taking into consideration the interactions between each algorithm. All the models in the ensemble are individually optimized with the suitable hyperparameter optimization method, which allows us to tailor the strategy to the model’s needs. Our approach aims to improve the ensemble’s performance, significantly enhancing the accuracy and robustness of clustering outcomes. Through this approach, we aim to enhance our understanding of PCOS and EC, potentially leading to diagnostic and treatment breakthroughs.

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Section: Introductionmentioning

confidence: 99%

Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches

Karadayı Ataş

2024

Mathematics

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The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review

Silva-Sousa,

Usuda,

Al-Arawe

et al. 2024

Stem Cells

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Advanced bioinformatics analysis, such as systems biology (SysBio) and artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL), is increasingly present in stem cell (SC) research. An approximate timeline on these developments and their global impact is still lacking. We conducted a scoping review on the contribution of SysBio and AI analysis to SC research and therapy development based on literature published in PubMed between 2000 and 2024. We identified an 8 to 10-fold increase in research output related to all 3 search terms between 2000 and 2021, with a 10-fold increase in AI-related production since 2010. Use of SysBio and AI still predominates in preclinical basic research with increasing use in clinically oriented translational medicine since 2010. SysBio- and AI-related research was found all over the globe, with SysBio output led by the (US, n = 1487), (UK, n = 1094), Germany (n = 355), The Netherlands (n = 339), Russia (n = 215), and France (n = 149), while for AI-related research the US (n = 853) and UK (n = 258) take a strong lead, followed by Switzerland (n = 69), The Netherlands (n = 37), and Germany (n = 19). The US and UK are most active in SCs publications related to AI/ML and AI/DL. The prominent use of SysBio in ESC research was recently overtaken by prominent use of AI in iPSC and MSC research. This study reveals the global evolution and growing intersection among AI, SysBio, and SC research over the past 2 decades, with substantial growth in all 3 fields and exponential increases in AI-related research in the past decade.

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Wound Healing of Boiologically and Chemically Syntehsized Gold Nanoparticles through Scratch Assay and Neural Network Modeling

Desai,

Ashok,

Wagle

et al. 2024

Preprint

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Gold nanoparticles (Au NPs) are commonly used as anti-haemorrhagic and antiseptic agents. Thus, their cytotoxicity should be studied before application. In this study, the Au NPs were synthesized using biological and chemical routes, and the samples were named as AU-BT and AU-C, respectively. The AU-BT were synthesized using three different extracts, i.e., turmeric, aloe-vera, and a mixture of turmeric aloe-vera. The cytotoxicity was studied using scratch assay on HEK-293 cell lines. The number of scratch assays was increased to validate the experimental wound healing results. Finally, a neural networking modeling was performed to predict the results of provided data in terms of the sample toxicity by healing the wound. The experimental results and the neural networking confirmed that the turmeric-derived Au NPs were the best among all the synthesized samples. Moreover, integrating metal NPs in wound healing studies introduces exciting possibilities for enhanced imaging and therapeutic interventions. The combination of advanced image analysis through models like AlexNet and the novel use of nanoparticles opens doors to improved wound care and a deeper understanding of the healing process.

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Machine Learning Approaches for Stem Cells

Cited by 3 publications

References 81 publications

Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches

Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches

The global evolution and impact of systems biology and artificial intelligence in stem cell research and therapeutics development: a scoping review

Wound Healing of Boiologically and Chemically Syntehsized Gold Nanoparticles through Scratch Assay and Neural Network Modeling

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