Read & Win: Standard and Super-Resolution Bioimaging Data Analysis
Over the last 25 years, there have been significant developments in the area of light microscopy for biomedical sciences, with new technologies emerging on a regular basis. Most of the data generated by these systems is image-based, and thus there has been a significant increase in the content and throughput of these systems. There is a new book which allows users to get up-to-speed on the mathematics, statistics, computing hardware and acquisition technologies required to correctly process and document data, i.e. Standard and Super-Resolution Bioimaging Data Analysis: A Primer. Written for both students and experience researchers in the biosciences, this text de-mystifies the array of image analysis modalities which have emerged in recent years, whilst aiding newcomers in bioimaging principles, mathematics, technologies and standards.
Win the book!
To have a chance of winning the book read Issue 1, 2019 of Imaging & Microscopy (page 12). As a subscriber you could read the issue already online or order you own copy (as a free trial copy). Take part in our competition and send your answer to firstname.lastname@example.org with the subject line Read & Win. All correct answers will be entered in a prize draw and the lucky winner will receive a copy of "Standard and Super-Resolution Bioimaging Data Analysis - A Primer".
Closing date: May 21, 2019.
Dr. Ann Wheeler
Ann Wheeler is the facility manager of the Advanced Imaging Resource at the Institute of Genetics and Molecular Medicine, University of Edinburgh. She completed her PhD in cell biology at University College London and Postdoctoral research at Imperial College, London and The Scripps Research Institute, USA. During her research career she consistently used emerging imaging methods, from TIRF, to Spinning disk microscopy and Fluorescent speckle microscopy to high content screening. In 2009 she took up an independent position at Queen Mary University London as the Light microscopy facility manager where, as well as running a Light Microscopy facility, she developed spinning disk super-resolution microscopy.
In 2014 she moved to the University of Edinburgh where she manages a large and diverse imaging resource termed AIR, has collaborated with industry developing the Dragonfly confocal system and is part of the award winning Edinburgh Super-resolution Imaging Consortium (ESRIC). She sits on the committee of the British Society for Cell Biology (BSCB) and the European Light Microscopy Initiative (ELMI). Her group are active participants in the Network of European Bioimage Analysts (NEUBIAS) project and recently hosted a training school for BioImage Analysis.
Interview with Ann Weeler:
What is your main focus in research, what is your main scientific interest?
Weeler: As an imaging facility manager my major focus, as it were, is light microscopy and specifically its application to molecular cell biology. I came into microscopy as a Cell Biology student who needed to find better ways to answer research questions in my PhD looking at the role of Rho GTPases regulating leukocyte migration. Since leukocytes are small and the actin and microtubule cytoskeleton are even smaller I soon found myself using cutting edge imaging methods. At the time there was no TIRF microscope in the UK specified for cell biology so I had to go to Mike Sheetz lab in Columbia University New York. There I really got the bug for developing microscopes to suit research purposes. This lead me to work with several emerging methods. Eventually I wanted to be the one to specify the microscopes myself. Super-resolution microscopy was new at the time. It’s been a lot of fun working with researchers applying these methods to molecular cell biology questions.
What was the reason to write the book?
Weeler: I’ve worked in and with several facilities and in all of these are PhD and Masters students who have been given image analysis questions to solve and there is no textbook currently available to give them a starting point. There are some excellent texts, including Wiley’s BioImage Data Analysis edited by Kota Miura which help get students going with scripting. However, for total beginners there is very little indeed available. If the student is in a core facility with a Bioimage Analyst, such as ours at the IGMM in Edinburgh, they may be able to access support. If not they will get stuck very quickly and there is a concern that misunderstanding image data leads to scientific misinterpretation.
What is the target audience for the book?
Weeler: The book was written for Undergraduate, Masters and PhD students who are working towards a qualification in Bioscience. Often these students will have little experience of advanced light microscopy from their undergraduate degree and almost no knowledge of Bioimage analysis. As part of the ELMI and Eurobioimaging project I am aware that in Europe (and in the UK) there are places where there is no Light Microscopy facility or the facility has no dedicated Bioimage Analyst. This book was written to help any researcher generating Bioimages using light microscopy analyse their data.
What knowledge is prerequisite for the book?
Weeler: Since we have written the book with new Masters and PhD students in mind we would assume an undergraduate level knowledge of Biochemistry or similar. The book is a primer so no pre-requisite knowledge at all is assumed. Effectively we take our readers from zero to hero!
What is the structure of the book?
Weeler: The book covers Bioimage analysis of most types of light microscopy experiment to date. It starts with three chapters introducing concepts of Bioimage digitization, ‘from nature to numbers’, image segmentation and quantification. All of which are pre-requisite for quantitative bioimage analysis. We then focus on FRET, correlation techniques, tracking super-resolution microscopy.
Which area of research benefits most from the super-resolution techniques?
Weeler: The obvious answer is any molecular cell biology question where the structures are too small to visualize using confocal microscopy. The Human Genetics Unit, which comprises the majority of our users focusses on gene regulation and the impact of gene dysregulation on disease. We have been able to provide quantitative analysis using super-resolution of the nucleus to make several ground-breaking discoveries. We also work very closely with cancer researchers, cell biologists and virologists. Since the ESRIC facility is open access we have a huge range of questions. Perhaps the most unusual was analysis of Coccoliths which are tiny single celled organisms live on the sea bed.
Would publishing the scripts used in the image analysis help spotting artefacts or errors?
Weeler: Yes, I am a strong believer in open access. Publishing scripts would also help reduce effort. Our imaging facility has a github site where we do have our scripts available (although I may need to have a look at when we last updated it now). Since we work in a Medical Research institute the scripts themselves are a flexible tool which are used for interrogation of Biological research. The script is, in 99% of cases, not the novel research. It is the means to access the data for the novel research. One question would be who would review these scripts? Mostly the peer review in the journals we publish in is carried out by expert biologists not expert bio-ime analysts..
Will artificial intelligence gain importance in image analysis?
Weeler: I believe it already is important. There are several trainable image analysis tools, including the Weka in Image J and Rapid learning in Icy which make use of machine learning. Particularly in analysis of pathology images and big image datasets AI will become increasingly important. This means the role of the bioimage analyst will change. Bioimaging currently can only measure 10s to 100’s of data points. Systems which increase the scale of experiments such as high content screening and pathology slide scanners are becoming increasingly used to increase the number of datapoints collected and breadth of experiments. So naturally the volume of image data produced is increasing. We already use scripts for more commonly to analyze data now compared to 5 years ago. In 5 years time I would expect to see AI used more frequently.
Standard and Super-Resolution Bioimaging Data Analysis
Wheeler, Ann / Henriques, Ricardo (Editors)
December 2017, Hardcover
Wiley & Sons and Royal Microscopy Society