Insight From Imaging
November 2-8, 2025
HHMI Janelia Research Campus
Course Directors:
Teng-Leong Chew and Rachel M. Lee (HHMI Janelia)
Jump to: Lecture Notes | Labs and Analysis Sessions | Further Reading​
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COURSE INFORMATION
Course Schedule [PDF]
Course Instructors [PDF]
Ice Breaker Introduction Slides [PDF]
Imaging Rotation Groups [PDF]
Microscope Map [PDF]
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​​​​​​Join the conversation on BlueSky: @aicjanelia.bsky.social‬ | #InsightFromImaging​​​​​​​​​​
Share your photos of the course here: Google Drive Folder​​​​​​​​ | Group Photo | Silly Group Photo
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DATA & DOWNLOADS
​Fiji Program
You should use this version even if you already have Fiji installed on your laptop.
Do not update Fiji after installation.
Click here to download for Mac
Click here to download for Windows
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Sample Images for Fiji Lectures
339 MB of images [download 168 MB .zip]
Additional Images
Segmented neurons for object-based co-localization: green and red
Example for color segmentation: H_E.tif​
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A1: Speed Analysis Lab Data Set
8.3 GB of images [download 4.8 GB .zip file​​]
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Data for "From Hypothesis to Results" Activity
63 MB of images [download 17 MB .zip]​
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Introduction Slide Template: Intro due Oct 31
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USEFUL LINKS
Free​ Janelia Fluor dyes at dyes.janelia.org.
Plasmids from the Integrative Imaging team on Addgene.
Directions to Janelia laundry [PDF]
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Lecture Notes
L01 Informative Experimental Design
An introduction to the workshop
Getting started with image analysis
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L03 Imaging Parameters: Resolution
How to choose your imaging resolution
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Turning pixel map into discrete objects
How to choose your imaging speed
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Tracking objects and measuring their motion
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L07 Imaging Parameters: Light-Biology Interaction
Considerations for sample health during imaging
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L08 From Hypothesis to Results Discussion
Considerations for going from idea to quantitative results
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How to achieve depth during imaging​
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Intensity-based co-localization measurements
2024 Workshop Materials: Extended Lecture | Class Activity Instructions | Example Data [900 MB .zip]
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Lifetime imaging, polarization, spectral imaging, and more
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Machine learning in image analysis
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Sample preparation and correlative approaches
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DISCUSSION SESSIONS
What resolution is necessary?
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How are temporal parameters chosen?
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How does the sample impact imaging?
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What depth approach is appropriate?
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Lab and Analysis Sessions
LAB SESSIONS
Paxillin and actin staining protocol
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ANALYSIS AND ACTIVITY SESSIONS
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Tracking practical
Google Colab Analysis Notebook
Upload group presentations here
A2 From Hypothesis to Results
Developing an analysis workflow
Upload group presentations here
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Hypothesis Formulation Challenge
Upload group presentations here
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Further Reading
When Light Meets Biology: How the Specimen Affects Quantitative Microscopy
Michael Reiche, Jesse Aaron, Ulrike Böhm, Michael DeSantis, Chad Hobson, Satya Khuon, Rachel Lee, and Teng-Leong Chew
J. Cell Sci. 2022
doi:10.1242/jcs.259656
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A guide to accurate reporting in digital image acquisition - can anyone replicate your microscopy?
John M. Heddleston, Jesse S. Aaron, Satya Khuon, Teng-Leong Chew
J Cell Sci 2021
doi: 10.1242/jcs.254144
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A guide to accurate reporting in digital image processing - can anyone reproduce your microscopy?
Jesse S. Aaron, Teng-Leong Chew
J Cell Sci 2021
doi:10.1242/jcs.254151
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Eric C. Wait, Michael A. Reiche, Teng-Leong Chew
J Cell Sci 2020 133.
doi:10.1242/jcs.250027
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Practical considerations in particle and object Tracking and Analysis
Jesse S. Aaron, Eric Wait, Michael DeSantis, Teng-Leong Chew
Curr Prot Cell Biol 2019 e88.
doi: 10.1002/cpcb.88
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Image co-localization – co-occurrence versus correlation
Jesse S. Aaron, Aaron B. Taylor, Teng-Leong Chew
J Cell Sci 2018 131: jcs211847
doi: 10.1242/jcs.211847
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Analysis of Image Similarity and Relationship
Jesse S. Aaron, Teng-Leong Chew
In: Jerome W., Price R. (eds) Basic Confocal Microscopy.
Springer, Cham
doi:10.1007/978-3-319-97454-5_11
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Imaging methods are vastly underrepresented biomedical research
Guillermo Marques, Thomas Pengo, Mark A. Sanders
eLife 2020;9:e55133
doi: 10.7554/eLife.55133
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Model-free quantification and visualization of colocalization in fluorescence images
Aaron B. Taylor, Maria S. Ioannou, Jesse S. Aaron, Teng-Leong Chew
Cytometry Part A 2018
doi: 10.1002/cyto.a.23356
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Perceptually accurate display of two greyscale images as a single colour image
Aaron.B. Taylor, Maria.S. Ioannou, Takashi Watanabe, Klaus Hahn, Teng-Leong Chew
J. Microscopy 2018 268: jmi.12588
doi:10.1111/jmi.12588
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Automatic and quantitative measurement of protein-protein colocalization in live cells
Costes, S. V., Daelemans, D., Cho, E. H., Dobbin, Z., Pavlakis, G. and Lockett, S.
Biophys. J 2004 86: 3993-4003.
doi: https://doi.org/10.1529/biophysj.103.038422
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Seeing is believing? A beginners' guide to practical pitfalls in image acquisition
Alison J. North
J. Cell Biol. 2006 172: 9-18
doi: 10.1083/jcb.200507103
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Accuracy and precision in quantitative fluorescence microscopy
Jennifer C. Waters
J. Cell Biol. 2009 187: 1135-1148
doi: 10.1083/jcb.200903097
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Protein-Retention Expansion Microscopy (ExM): Scalable and Convenient Super-Resolution Microscopy
Paul Tillberg
Methods Mol Biol. 2021;2304:147-156.
doi: 10.1007/978-1-0716-1402-0_7
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What If Scientists Shared Their Reagents for Free?
Amanda Heidt
The Scientist, July 2022 Issue 2
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Believing is seeing – the deceptive influence of bias in quantitative microscopy
Lee, R.M., Eisenman, L.R., Khuon, S., Aaron, J.S. and Chew, T.-L.
J. Cell Sci. 2024 137 (1): jcs261567
doi: 10.1242/jcs.261567
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Practical considerations for quantitative light sheet fluorescence microscopy
Hobson, C.M., Guo, M., Vishwasrao, H.D., Wu, Y., Shroff, H., Chew, T.-L.
Nat. Meth. 2022 19, 1538-1549
doi: 10.1038/s41592-022-01632-x
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Combining multiple fluorescence imaging techniques in biology: when one microscope is not enough
Hobson, C.M. and Aaron, J.S.
MBoC 2022 33 (6)
doi: 10.1091/mbc.E21-10-0506
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Ellen Quarles, Leanna Eisenman, Mai Rahmoon, and Teng-Leong Chew
EASI-FISH for thick tissue defines lateral hypothalamus spatio-molecular organization
Yuhan Wang, et. al.
Cell 2021 184 (26)
doi: 10.1016/j.cell.2021.11.024
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Deep-tissue transcriptomics and subcellular imaging at high spatial resolution
Valentina Gandin, et. al.
Science 2025 388 (6744)
doi: 10.1126/science.adq2084
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SuperPlots: Communicating reproducibility and variability in cell biology
Samuel J. Lord, Katrina B. Velle, R. Dyche Mullins, and Lillian K. Fritz-Laylin
Journal of Cell Biology 2020 219 (6): e202001064
doi: 10.1083/jcb.202001064
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