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Medicine and the Arts: Humanising Healthcare
Exploring Play: The Importance of Play in Everyday Life
Songwriting: Writing the Lyrics
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Explore the evolution of genome editing and programmable medicine with CRISPR pioneer Feng Zhang and his lab members, discussing advancements and future potential in this field.
Explore cutting-edge research and developments in rare disease therapies through expert talks on genetics, drug development, biomarkers, and patient-centric approaches.
Explore generative AI applications in single-cell response modeling, covering data integration, representation learning, and multiomics analysis for biomedical insights.
Explore sparsity in epistatic interactions to enhance fitness function modeling. Learn about Walsh-Hadamard transform, Graph Fourier transforms, and Epistatic Net for improved protein function prediction.
Explore contrastive latent variable models for analyzing differential expression in sequencing data, enhancing case-control comparisons in transcriptomics with novel approaches to capture condition-specific variations.
Explore genome harmonization techniques for deeply sequenced data, covering quality control, structural variants, and PCA analysis using cloud computing.
Explore suSIEx, a cutting-edge method for analyzing genetic data in medical and population genetics. Learn its principles, applications, and potential impact on understanding complex traits and diseases.
Explore ethical considerations in using population descriptors for genomic research. Learn from experts about the importance of thoughtful group categorization in science and society.
Explore natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing. Learn about experiment design, data quality, analysis techniques, and biological insights in single-cell genomics.
Explore groundbreaking research by emerging scientists on neurodegenerative diseases, cardiac health, infectious disease diagnosis, and rare genetic disorders.
Explore mass spectrometry-based proteomics techniques for biomarker discovery and pQTL mapping in this workshop by Lili Niu from the University of Copenhagen.
Explore deep learning models for integrating patient-level multi-omics data, focusing on supervised and unsupervised approaches for predicting outcomes and uncovering latent representations in genomics.
Explore deep learning techniques for genomic discovery, focusing on high-resolution assays, footprint shapes, and bias correction methods in neural networks.
Explore Mendelian randomization's evolution, from its genetic roots to modern applications in epidemiology. Gain insights into its capabilities, limitations, and potential future developments in phenotypic causation research.
Explore spatial copy number alteration detection in Slide-seq-like spatial transcriptomics data. Learn basic genetics principles related to human populations and disease.
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