Matches, Mismatches, and Methods: Multiple-View Workflows for Energy Portfolio Analysis.

The energy performance of large building portfolios is challenging to analyze and monitor, as current analysis tools are not scalable or they present derived and aggregated data at too coarse of a level. We conducted a visualization design study, beginning with a thorough work domain analysis and a characterization of data and task abstractions. We describe generalizable visual encoding design choices for time-oriented data framed in terms of matches and mismatches, as well as considerations for workflow design. Our designs address several research questions pertaining to scalability, view coordination, and the inappropriateness of line charts for derived and aggregated data due to a combination of data semantics and domain convention. We also present guidelines relating to familiarity and trust, as well as methodological considerations for visualization design studies. Our designs were adopted by our collaborators and incorporated into the design of an energy analysis software application that will be deployed to tens of thousands of energy workers in their client base.

Cryptic protein fragments as an emerging source of peptide drugs.

This commentary evaluates the newly proposed concept of crypteins - peptides with embedded cryptic activity - as a source of peptide drugs. Although several crypteins are undergoing advanced clinical trials, and one cryptein, adrenocorticotropic hormone (ACTH), is already widely used as a therapeutic, crypteins remain an underappreciated class of biopharmaceuticals. The systematic exploitation of crypteins provides a novel source of peptide drugs, and may also provide templates for developing peptidomimetic compounds. In addition, crypteins appear to offer several advantages over synthetic protein libraries and other protein scaffolds.

Biochips beyond DNA: technologies and applications.

Technological advances in miniaturization have found a niche in biology and signal the beginning of a new revolution. Most of the attention and advances have been made with DNA chips yet a lot of progress is being made in the use of other biomolecules and cells. A variety of reviews have covered only different aspects and technologies but leading to the shared terminology of "biochips." This review provides a basic introduction and an in-depth survey of the different technologies and applications involving the use of non-DNA molecules such as proteins and cells. The review focuses on microarrays and microfluidics, but also describes some cellular systems (studies involving patterning and sensor chips) and nanotechnology. The principles of each technology including parameters involved in biochip design and operation are outlined. A discussion of the different biological and biomedical applications illustrates the significance of biochips in biotechnology.

Biomedical applications of protein chips.

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.

Emerging high-throughput drug target validation technologies.

Identifying the right target for drug development is a critical bottleneck in the pharmaceutical and biotech industries. The genomics revolution has shifted the problem from a scarcity of targets to a surplus of putative drug targets. As the validity of a target cannot be simply inferred from correlative data, the key is confirmation of the causative role of a gene product in a particular disease. It should therefore be recognized that an effective therapeutic strategy requires an appropriate target validation technology to verify the right target.