Machine learning algorithmsDeep learningStem cell characterisationStem cell profilingRegenerative medicineMachine learning (ML) enables high-throughput analysis of multimodal data generated from stem cell experiments such as gene expression data, images of cells, or proteomic data. In this review, we ...
Experimental approaches to study tissue specificity enable insight into the nature and organization of the cell types and tissues that constitute complex multicellular organisms. Machine learning provides a powerful tool to investigate and interpret tissue-specific experimental data. In this Review, we firs...
All the preprocessing, filtering, and machine learning analysis was conducted using Waikato Environment for Knowledge Analysis (WEKA) 3.8.6 machine learning toolkit along with R scripts.Abbreviations AD-MSCs: Adipose tissue derived mesenchymal stem cells ALT: Alanine transaminase AST: Aspartate ...
Machine Learning Approaches for Stem Cells Mazlee Mazalan Tien-Dung Do Effirul I. Ramlan Current Stem Cell Reports (2023) Moving Towards Induced Pluripotent Stem Cell-based Therapies with Artificial Intelligence and Machine Learning Claudia Coronnello Maria Giovanna Francipane Stem Cell Reviews ...
The cells colored/highlighted in Yellow tells you which model scored based for that particular evaluation matrix. Here we can see Ridge Classifier scored best using Accuracy and Precision. While the Linear Discriminant Analysis model was best using F1 score, Kappa and MCC. print(best_model) RidgeC...
(MPRAs) can directly quantify the activity of hundreds of thousands of CREs across cell types8,18,19,20,21,22, providing insights into regulatory syntax and cellular specificity23,24,25,26,27. Second, deep learning approaches have proven to be effective tools for predicting the relationships ...
The NMP (nanomechanical properties) data was then utilized by an ML (Machine Learning) algorithm to demonstrate various classifications and their corresponding accuracies to exhibit the importance of distinguishing cell-ECM NMPs and ML-driven data classification approaches in this paradigm. 2. ...
We will require a Q table of millions of cells. The game of chess and Go will require an even bigger table. This is where Deep Q-learning comes for the rescue. It utilizes a neural network to approximate the Q value function. The neural networks recipe states as an input and outputs...
Epigenetics studies inheritable and reversible modifications of DNA that allow cells to control gene expression throughout their development and in response to environmental conditions. In computational epigenomics, machine learning is applied to study various epigenetic mechanisms genome wide. Its aim is to...
Automated human induced pluripotent stem cell culture and sample preparation for 3D live-cell microscopy Article 12 December 2023 A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei Article 11 January 2021 Segmentation aware probabilistic phenotyp...