Effective Scientific Schematic Development

Students will learn to design clear, visually engaging scientific schematics that effectively communicate complex research concepts, methodologies, and findings. Through hands-on instruction, students will gain experience creating research workflow diagrams, conceptual frameworks, graphical abstracts, and scientific illustrations using accessible tools such as BioRender, Canva, diagrams.net (Draw.io), Microsoft PowerPoint, Google Slides, and Inkscape. Students will explore how to select appropriate visual representations, organize complex scientific information, and apply principles of visual clarity, scientific accuracy, color coordination, and effective labeling. Emphasis will be placed on developing professional, publication-ready figures that adhere to scientific communication standards and journal guidelines. By the end of the program, students will be equipped to independently develop high-quality scientific schematics for research manuscripts, conference posters, presentations, and graphical abstracts. See sample schematics (right).

SPECK method workflow showing normalization, rank-revealing reduction, gene-expression thresholding, and reconstruction of an m×n single-cell RNA-seq matrix.
STREAK schematic showing receptor gene-set construction, gene scoring, clustering, and thresholding to estimate cell-specific receptor abundance from scRNA-seq and CITE-seq data
Method schematic showing Cytosig cytokine gene-set construction and VAM scoring of simulated single-cell RNA-seq data, producing cell-specific cytokine scores and validation heatmaps.
Diagram showing ligand-receptor interaction characterization for spot-level spatial transcriptomics, including RRR spot scores, Euclidean distances, degree centrality, and reconstructed rank-reduced interaction matrix.
Diagram of an autoencoder-based denoising and supervised cell-signaling estimation model, showing an input adjacency matrix, encoder-decoder layers, bottleneck, and degree-centrality output.
Diagram showing MouSSE single-cell RNA-seq matrix construction and positive or negative cytokine gene-set scoring using SCAPE.