David Warren's List: Biology Resources for Kaila

• Scitable currently concentrates on genetics, the study of evolution, variation, and the rich complexity of living organisms.

• A main reason for the increased accessibility and use of visualization software has been the advances in computer hardware and network access. Many visualization tasks that previously required expensive and specialized hardware can now be easily managed with a standard personal computer. However, an equally important factor has been the development of a wide range of methods and tools specialized in visualizing specific kinds of biological data. In this Supplement, we discuss over 200 tools selected from the much greater number now available. This diversity of tools can be confusing, but it is probably unavoidable, given the diverse nature of the biosciences. In fact, in many cases, biologists still find that their exact requirements are not met by current tools and often have to create custom solutions. This has helped spur a growing trend to allow reuse of visualization software, either by means of open source software libraries (for example, http://www.vtk.org/) or by means of architectures specifically designed to allow extensions (for example, Cytoscape⁶).
• Although visualization methods and tools have greatly improved, there has also been an exponential increase in the size and complexity of data sets studied in biology. A common challenge faced by many biologists is how to benefit from this data deluge without being overwhelmed by it. Visualization is clearly part of the solution; however, the sheer number and diversity of tools available can make the problem worse. Below we discuss several recent advances toward addressing these issues.
• These principles are increasingly being adopted by developers of visualization tools for biologists.
• Unfortunately, improvements may be slow, because work on usability is usually less rewarded in science than is research on new methods.
• And projects from the structural biology and microscopy communities aim to integrate biological data on the basis of a cellular coordinate framework (for example, Visible Cell²⁵ and others²⁶) by synthesizing multiscale data, including data from cellular tomograms, cryo-electron microscopy, and atomic-detail three-dimensional structures, as well as inventories of expressed proteins, estimations of organelle shapes and distributions, and protein localizations and gradients. Probably no single framework will suit all biologists; however, the goals of these different efforts may eventually produce a standardized visualization environment that allows seamless integration of biological data (Fig. 1).
• Soon, biologists may be able to seamlessly move between data from tissue, cellular and molecular scales, as well as data from genomes, networks and pathways. Many of these data will be organized around a cellular coordinate framework, and visualization of biochemical pathways will allow increasingly detailed representations of cellular topology and of proteins. For instance, selecting a tissue (left image) could automatically show micrographs of cell types; selecting a cell type could show relevant pathways (center image); selecting a protein from the pathway could access micrographs showing the cellular distribution and effects of knockdown experiments (bottom, center); in addition, selecting the protein could show atomic-detail three-dimensional structural information, sequence features, alignments and genomic location. Many of these interoperations are already being used today. Images courtesy of ClearScience (drawing), iStockPhoto (lung X-ray), Univ. of Kansas Medical Center (lung histology), Digizyme and Cell Signaling Technology (pathway). Protein structure and sequence alignment made using SRS 3D; chromosome image from UCSC Genome Browser⁸.
• But all these efforts are still very much at the pioneering stage, and, to paraphrase Alan Kay, we could say that the revolution in biological data visualization hasn't started yet.

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• One of the most daunting tasks facing biologists is choosing from the multitude of tools available, and so the authors of each review highlight a selected fraction of available tools that are most likely to be of use. Because these tools can be very specialized and the writers themselves are developers of some of the tools, there is little comparative assessment. Instead, the reviews focus more on the challenges and methods behind the tools. The tools themselves, ranging from simple stand-alone software to complex integrated software packages, are conveniently listed in tables within each review, and links are provided so that readers may easily access the tools and evaluate which ones best meet their specific needs.