Lecture

Open-World Learning for Biomedical Data

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Description

This lecture discusses open-world learning for biomedical data, focusing on methods to leverage small datasets under different conditions. It covers the significance of single-cell multimodal omics, spatially resolved transcriptomics, and the challenges in generalizing across experiments. The instructor presents the development of novel machine learning paradigms for biomedical research, emphasizing the importance of discovering unknown phenomena and cell types. The lecture showcases the application of these methods in annotating spatially resolved single-cell data and the Human BioMolecular Atlas Program. It concludes with future directions in machine learning for biomedicine, including knowledge-grounded ML systems and multi-modal ML methods.

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Related concepts (32)

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Cell type

A cell type is a classification used to identify cells that share morphological or phenotypical features. A multicellular organism may contain cells of a number of widely differing and specialized cell types, such as muscle cells and skin cells, that differ both in appearance and function yet have identical genomic sequences. Cells may have the same genotype, but belong to different cell types due to the differential regulation of the genes they contain.

Cell potency

Cell potency is a cell's ability to differentiate into other cell types. The more cell types a cell can differentiate into, the greater its potency. Potency is also described as the gene activation potential within a cell, which like a continuum, begins with totipotency to designate a cell with the most differentiation potential, pluripotency, multipotency, oligopotency, and finally unipotency. Totipotency (Lat. totipotentia, "ability for all [things]") is the ability of a single cell to divide and produce all of the differentiated cells in an organism.

Online machine learning

In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.

Supervised learning

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).

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