Bioimage Informatics

It is no secret that imaging, and microscopy in particular, represents a substantial fraction of the manuscripts published in Nature Methods. Our very first focus issue, in fact, was on fluorescence imaging. When that focus was published in 2005 the term ‘bioimage informatics’ didn’t even exist. Even today, the term isn’t widely used and, unlike many other bioinformaticians, those who work on the development of algorithms and software tools for analysis of biological image data have few dedicated venues for discussing or publishing their work.

But computational techniques are becoming increasingly important in biological imaging and the people developing these tools increasingly see themselves as a distinct community. When we approached the community about publishing a focus issue on bioimage informatics there was an enthusiastic response and the results can be seen in our July issue and focus that went live today.

We hope that biologists using microscopy in their research find the information in the focus useful and that it stimulates them to try some of the tools now available and in development. Many of these tools have functionality designed to encourage community participation and aid in both the creation of new analysis methods and the communication of methods and protocols to other users.

Although these tools and the community developing them have come a long way since Wayne Rasband first released NIH Image, bioimage informatics is still in its relative infancy. As discussed in the focus editorial, algorithm development and usage will become even more important for biological microscopy and will change the way biologists perform and report their research.

New video functionality in online manuscripts

Data in research papers that is best presented in the form of videos gets short shrift compared to data that can be easily presented in figures and tables. Printing of representative video frames is a poor surrogate. Embedding videos in PDFs is possible but rare. Even online, where embedding videos in an HTML page is technologically easy, videos are usually provided only as links in the supplementary information for downloading video files.

This week, Nature Methods published two manuscripts from Keller and colleagues and Hufnagel and colleagues describing improved light-sheet microscopy technology that captures amazing time-lapse 3D images of fluorescently labeled cells in developing Drosophila embryos. To help showcase the beautiful videos containing this data we debuted new video functionality that Nature Publishing Group will be rolling out to other journals over time.

We invite you to watch these videos and let us know what you think about the new streaming video player, or the imaging method used to obtain this data. Some of the videos are very large and will take some time to start if you have a slow Internet connection but we hope that even in these cases you find this to be an improvement.

Of course, we still offer the ability to download the original video files supplied by the authors so you can see them in their original resolution, regardless of the speed of your connection.

What’s behind an fMRI signal?

In this month’s editorial we discuss the importance of gaining a deeper understanding of the signals underlying fMRI technology.

Despite the increased interest in this technology and the huge investments, we know very little about the underlying biology that produces these signals. This lack of understanding limits the type of information that can be obtained from this methodology and its utility to help us understand how our brains work.

We discuss new technological developments that might help address this question, including a research article by Dr. Helmchen and colleagues in this issue.

Dialogs between neuroimagers and cellular neurobiologists are critical to solve this question, as has been discussed before and funding institutions should give a higher priority to projects focused on gaining a deeper understanding of these complex signals.

Using the NIH RePORTER database we performed a search based on the following terms: ‘functional magnetic resonance imaging’ and ‘brain imaging’. We restricted the search to active projects starting on 1 January 2010 and we screened through the list of projects to remove those that were related to MRI but not fMRI. We then added up the total cost of all projects in the curated list. The number that we present in the piece is approximate and has not been scrutinized in detail. This way, we came up with the approximate amount of money that the US National Institute of Health has spent over different time periods in the last years. 

An exponential increase in scientific publications based on fMRI research has also been observed over the last years.

We’re curious to hear what you think of this!

Where’s your ground truth?

When using or developing experimental and observational methods it is crucial to assess the method performance in an effort to ensure that the information it provides reflects reality. For experimental biologists this often means conducting carefully chosen control experiments with alternative methods or different experimental settings. More rigorous assessment, particularly for high-throughput or large-scale methods, often requires the use of ‘ground truth’ or ‘gold standard’ data sets. But talk to different people and you will get different answers regarding what ‘ground truth’ or ‘gold standard’ data is. This often includes a nice historical explanation of where the term ‘ground truth’ comes from.

For developers of signal processing and image analysis algorithms though, the situation is clearer; the ground truth is the signal or image you start with. But add a living system into the mix and things get far more complicated. The Editorial in the November issue of Nature Methods discusses the challenges facing developers and users of algorithms for automated analysis of biological data, with a focus on image data. In short, traditional ground truth data is often insufficient. The addition of integrated-editing and change-logging capabilities to these software tools can increase the quality of the analysis, aid further algorithm development and increase the likelihood of biologists adopting the software in the first place.

Brains at work

Neuroscience is a field where much still needs to be learned and for that, technology development is increasingly necessary. Recent developments have greatly expanded our capacity to visualize the activity of neurons using genetically encoded fluorescent probes and optogenetic tools now enable precise modulation of this activity.

But the brain is contained in a protective skull and peeking into it is usually an invasive process. In this month’s editorial we discuss recent technical developments and future prospects that will take us a step closer to a minimally invasive form of ‘transcranial neuroscience’. Despite the big progress, much work remains but we are hopeful that with the right technology and motivation, the field will soon approach the holy grail of performing non-invasive cellular-level functional studies of the entire brain.

Any thoughts about this? Tell us what’s on your mind!

Data overload

How do you handle terabytes of data? That is a question that more and more investigators must face, on a weekly basis.

Are you one of them? Light-sheet fluorescence imaging, for example, generates so much data in each experimental run that handling and storing the raw data is a challenge. Next-generation sequencing is another, much more ubiquitous, case.

Read the July issue editorial “Byte-ing off more than you can chew” and let us know about your own experience, problems and practical (or impractical) solutions.

Increasing your fluorescence signal using pulsed excitation

Stefan Hell and colleagues propose that the use of pulsed excitation with a delay of at least one microsecond between pulses can dramatically reduce photobleaching and increase the effective fluorescence signal in both single and multi-photon fluorescence microscopy. Is this something you would consider trying in your lab? Do you think the described benefits are worth the necessary equipment changes?

Read the paper here and then add your opinion.