Visual Communication in Biology: Making Images, Structures, Data Figures and Model Diagrams (Janet Iwasa)
Janet Iwasa outlines categories of biological visualization, from microscopy and live-cell imaging to molecular structures derived from cryo-EM and crystallography, charts and tables, and model diagrams that explain mechanisms. She recommends describing the process first, then sketching early and often with pen and paper before using software, using color to distinguish data classes or subunits, and using charts such as bar graphs for quantitative data. She also points to the Nature Methods 'Points of View' series (2011–2013) by Bang Wong and colleagues and the 'Points of Significance' articles. The talk teaches research communication methods rather than specific research findings, and is useful for researchers preparing figures for talks and papers.
Categories of visualization: from microscopy images and live-cell imaging, to molecular structures derived from cryo-EM/crystallography (spatial information), then charts/tables (graphically representing non-spatial data), and 'model diagrams' used to explain mechanisms.; Model diagram workflow: first describe the process (where in the cell it happens, which proteins are involved), then use sketches to make the mechanism clear; the author emphasizes 'sketch early and often,' and sketches can in turn help design experiments.; Tools and color: it is recommended not to start with software, but with pen and paper first; color is good for distinguishing different classes of data or subunits, but for quantitative data, charts (e.g., bar graphs) are more accurate than spatial schematics.; Resources: recommends the Nature Methods (2011–2013) 'Points of View' data visualization series by Bang Wong et al., and the 'Points of Significance' statistical visualization articles.; Positioning: instruction in research communication methods, not specific scientific findings; of practical value to researchers making figures for talks/papers.
- Categories of visualization: from microscopy images and live-cell imaging, to molecular structures derived from cryo-EM/crystallography (spatial information), then charts/tables (graphically representing non-spatial data), and 'model diagrams' used to explain mechanisms.
- Model diagram workflow: first describe the process (where in the cell it happens, which proteins are involved), then use sketches to make the mechanism clear; the author emphasizes 'sketch early and often,' and sketches can in turn help design experiments.
- Tools and color: it is recommended not to start with software, but with pen and paper first; color is good for distinguishing different classes of data or subunits, but for quantitative data, charts (e.g., bar graphs) are more accurate than spatial schematics.
- Resources: recommends the Nature Methods (2011–2013) 'Points of View' data visualization series by Bang Wong et al., and the 'Points of Significance' statistical visualization articles.
- Positioning: instruction in research communication methods, not specific scientific findings; of practical value to researchers making figures for talks/papers.
Source: YouTube