activity based proteomics: Identification and analysis of changes in active proteins in different cell types and under different conditions ... addressing the biochemical mechanisms of disease more directly than standard genomics and proteomics techniques.

allosteric ribozymes (allozymes): Pharmaceutical biology glossary Potential for use in proteomics.

annotation- proteins: In SWISS- PROT, as in most other sequence databases, two classes of data can be distinguished: the core data and the annotation. For each sequence entry the core data consists of the sequence data, the citation information (bibliographical references), and the taxonomic data (description of the biological source of the protein), while the annotation consists of the description of the following items: Function(s) of the protein, Post- translational modification(s). For example carbohydrates, phosphorylation, acetylation, GPI- anchor, etc., Domains and sites. For example calcium binding regions, ATP- binding sites, zinc fingers, homeobox, kringle, etc., Secondary structure, Quaternary structure, Similarities to other proteins, Disease(s) associated with deficiencie(s) in the protein, Sequence conflicts, variants, etc.

applied proteomics: Current applications of proteomics seem to be focusing on toxicology and drug target identification and target validation.

bait: The basic format of the yeast-two hybrid system involves the creation of two hybrid molecules, one in which the "bait" protein is fused with a transcription factor, and one in which the "prey" protein is fused with a related transcription factor. If the bait and prey proteins indeed interact then the two factors fused to these two proteins are also brought into proximity with each other. As a result a specific signal is produced, indicating an interaction has taken place.

cell signalling proteomics: Using an antibody- based detection system that is proprietary to Kinexus called Kinetworks, over 100 proteins can be selectively tracked on a single SDS-PAGE minigel with 250 µg of crude protein extract. Kinexus has developed several commercial screens for the specific analysis of panels of protein kinases, protein phosphatases, phosphoproteins, cell cycle proteins, heat shock/ stress proteins and apoptosis proteins. Many of these regulatory proteins are produced at low levels that they not detected by traditional 2D gel- based approaches. We have observed profound differences in the expression, phosphorylation states and subcellular locations of these regulatory proteins in hormone-, drug- and toxin-treated cultured cells and in tissue biopsies from animal and human patient samples. This information is being used to map novel cell signalling pathways through bioinformatic analyses.

chemical proteomics: To link new proteins with known catalytic activities, proteome- scale screens for generic enzyme activities (e.g. protease and phosphatase) should be implemented ... Although it is impossible to screen for chemical reactions that are unknown, in theory, identifying small molecules that bind to the new proteins may elucidate clues to new activities. These ligands might be found by screening the new proteins against diverse chemical libraries using existing methods such as NMR spectroscopy, microcalorimetry, or microarrays. The general concept of ascribing function to new proteins by discovering small molecule ligands might be referred to as chemical proteomics.

comparative proteomics: The C. elegans proteome was used as an alignment template to assist in novel human gene identification. Among the available 18,452 C. elegans protein sequences, our results indicate that at least 83% had human homologous genes, with 7954 records of C. elegans proteins matching known human gene transcripts.

computational proteomics: Large- scale generation and analysis of 3D and 4D protein structural information and the application of structural knowledge across all life science disciplines.

directed protein evolution: We have developed an integrated program for the discovery and production of antibody mimetics that are screened for microarray applications. Using our proprietary directed protein evolution technology, PROfusion, stable binding proteins are rapidly produced with high affinity and specificity for their target antigens. Automation of the PROfusion system, coupled with an automated E. coli- based protein expression system, has allowed for the high- throughput generation of binders at low cost. Dr. Richard W. Wagner, Research, Phylos, Inc. "Development of an Automated Directed Protein Evolution Engine to Produce High- Affinity Binders for Protein Microarrays Protein Arrays: Technology and Applications: PepTalk January 7- 8, 2002 San Diego CA

dissociator assays: A collective term for yeast- one hybrid, yeast- two hybrid or yeast- three hybrid assays.

environmental proteomics: Many environmental chemicals interact directly with cellular proteins to modify protein functions and interactions. Environmental agents also may affect gene expression and presumably the levels of protein products of those genes. ... This new Core was developed to promote the integration of proteomics technologies into studies of the health effects of environmental agents. Investigators in the Environmental Proteomics Research Core use and adapt these technologies, particularly protein separations and mass spectrometry to investigate the interplay of environmental agents and the proteome. The overall goal of the Environmental Proteomics Research Core is to promote interdisciplinary, collaborative research into how environmental agents affect cellular proteomes.

Expressed Protein Tags EPTs: Multi- cellular organisms have been evolving a system with which they can discriminate between cells of their own origin and other adventitious cells or cells which have been infected with intracellular pathogens. To achieve this goal, a family of receptors, known as multi- ligand receptors (MLR), have evolved to be remarkably promiscuous binders of peptide ligands. The MLR-bound ligands are derived from degradation intermediates of cellular proteins. Typically, these ligands are 8-12 amino acids in length and have been coined by CANVAS as "expressed protein tags" or EPTs. EPTs are of sufficient length to differentiate particular proteins and/ or individual genes. Each MLR has a single binding site and thus contains a single EPT copy.

functional glycomics: At the present time approximately 110 glycogenes which encode glycosyltransferases and related genes have been cloned. Even though some of the biological functions of those genes have been elucidated, most of the actual functions of these genes continue to be obscure, and limited information is available in terms of their pathophysiolgical significance. Therefore in order to clarify the functional significance of these genes, one of the major strategies is focused on the identification of likely target molecules in vivo and the identification of their functional significance. Knock out or transgenic mice have already been reported for several glycogenes and currently available information indicate that some are lethal and some lead to interesting phenotypic changes.

functional proteomics: Relating function to gene expression, protein- protein interactions.

Is yielding large databases of interacting proteins and extensive pathways maps of these interactions are being scored and deciphered by novel high throughput technologies. However, traditional methods of screening have not been very successful in identifying protein- protein interaction inhibitors.

The identification and measurement of changes in concentration of specific proteins that cells make as a result of their genetic response to specific toxicants and how these proteins are related

high- throughput proteomics: Following the publication of the draft of the human genome sequence, the critical question to address now is: how will this information be used for drug target discovery and selection? It is becoming increasingly widely recognised that mechanisms underpinning disease mechanisms involve only specific protein isoforms. Therefore, to design effective therapeutic intervention, the identification of all protein isoforms coded by a particular gene, as well as information on what their structure, function and expression patterns represents is required. Unfortunately current computational gene predictions give only limited and partially accurate views on gene structure and products. High throughput proteomics is the only possible way to unambiguously identify and map protein coding genes in the human genome.

A bioinformatic approach was used to identify all putative genes from human chromosome 21, and almost all of them have been expressed in a semi- automated process. The resulting proteins and peptides were used to create antibody reagents. Labeled antibodies have been used to carry out functional proteomic studies, with particular emphasis on expression localization. The use of tissue arrays has facilitated the throughput of these studies. Comparisons of protein expression results with gene expression data will also be discussed.

homointeraction: A lot of proteins interact with themselves.

Human Proteome Organisation HUPO: The reason for creating HUPO is to assist in increasing the awareness of this discipline of science across society, particularly with regard to the Human Proteome Project and to engender a broader understanding of the importance of proteomics and the opportunities it offers in the diagnosis, prognosis and therapy of disease. As a global body it will also have the objective of fostering international cooperation across the proteomics community and of promoting scientific research in an on- going manner around the world..

Human Proteomics Initiative: http://www.expasy.ch/sprot/hpi/ Swiss Institute of Bioinformatics' major project to annotate all known human sequences according to the quality standards of SWISS- PROT. This means providing, for each known protein, a wealth of information that include the description of its function, its domain structure, subcellular location, post- translational modifications, variants, similarities to other proteins, etc.

interaction proteomics: Protein- protein interactions lie at the heart of most cellular processes. A complete understanding of cellular function depends on a full characterization of the complex network of cellular protein- protein associations. Alternative proteomics technologies are being developed to complement the two- hybrid system. These methods reveal direct protein- protein interactions by using protein affinity chromatography. Protein affinity chromatography, as developed by Greenblatt, Alberts, and colleagues, has the disadvantage of requiring purified proteins as reagents, but it is superior to the two- hybrid approach because it generates fewer false positives and is more amenable to high- throughput screening.

interologs: Protein interaction maps have provided insight into the relationships among the predicted proteins of model organisms for which a genome sequence is available. These maps have been useful in generating potential interaction networks, which have confirmed the existence of known complexes and pathways and have suggested the existence of new complexes and or crosstalk between previously unlinked pathways. However, the generation of such maps is costly and labor intensive. Here, we investigate the extent to which a protein interaction map generated in one species can be used to predict interactions in another species.

microbial proteomics: Bacterial genomes encode all possible virulence determinants, vaccine candidates, and potential drug targets. Further, a completed genomic sequence establishes a basis for high throughput analysis of the proteins expressed (i.e., the proteome). Respiratory pathogens have been among the first to have their genomes entirely sequenced.

Mycoplasma pneumoniae harbors the second smallest genome of any self-replicating life form and encodes 679 putative proteins. These genome- predicted proteins will be correlated with those actually present, detecting any biological event that generates a protein of different molecular composition than that predicted. These include sequence or reading frame errors, imprecise bioinformatics, co- or post- translational modifications, and mutational or proteolytic strategies for antigenic variation.

MudPIT Multidimensional Protein identification Technology: We will describe a largely unbiased method for rapid and large- scale proteome analysis via multidimensional liquid chromatography, tandem mass spectrometry, and database searching via the SEQUEST algorithm named multidimensional protein identification technology (MudPIT). The method has been applied to the analysis of yeast total cell lysates. Categorization of the proteins identified demonstrated this technology's ability to detect and identify proteins rarely seen in proteome analysis including integral membrane proteins from several cellular compartments and low abundance proteins like transcription factors and protein kinases. Of particular interest was our identification of 131 proteins with three or more predicted transmembrane domains.

phyloproteomics: Identification of unknown bacterial isolates based on similarities within protein biomarker databases.

physiological proteomics: Proteomics relying on two- dimensional (2-D) gel electrophoresis of proteins followed by spot identification with mass spectrometry is an excellent experimental tool for physiological studies opening a new perspective for understanding overall cell physiology. This is the intriguing outcome of a method introduced by Klose and O'Farrell independently 25 years ago. Physiological proteomics requires a 2-D reference map on which most of the main proteins were identified. ... A big challenge for future studies is to provide an experimental protocol covering the fraction of intrinsic membrane proteins that almost totally escaped detection by the experimental procedure used in this study.

post-proteomics: Companies are taking position at the end stages of drug discovery in the hopes that industry- wide efforts in gene expression, protein expression, protein- protein interaction and other proteomic studies will yield many disease targets that must have their function verified. But to become a marketable solution for the industry, they must significantly increase the scale of functional experiments such as animal models and cell assays that, historically, have not been easily scaled.

prey: Interacting proteins captured in protein complexes using a bait.

protein activity: Unraveling the mystery of protein activity is one of the largest challenges in scientific research and a key driver in the development of tools that enable the quick identification of high- quality targets. Current proteomics technologies can only identify already known proteins or proteins predicted from genomic data. MDS Proteomics uses PepSea to go one step beyond, enabling the identification of unknown proteins with no prediction necessary. PepSea also can, in seconds, determine the location and identity of human genes that encode the proteins. Because of the error tolerance inherent in the PepSea algorithm, proteins can even be identified regardless of intervening sequences, which make up the majority of human DNA.

protein and mRNA data: Although the relationship between mRNA and protein levels is vague for individual genes, some of the statistics for broad categories of protein properties are much more robust... In contrast to the differences between mRNA and protein data for individual genes, the broad categories show that the transcriptome and translatome populations are remarkably similar; both contain roughly the same proportions of secondary structure and functional categories. Moreover, this contrasts the difference with the genome, which appears to have a distinctly different composition of functional categories. This illustrates that we get a more consistent picture when we average across the population, i.e. there is broad similarity between the characteristics of highly expressed mRNA and highly abundant proteins.

protein- carbohydrate interactions: Are now recognized to be important mediators of cell communication. In the last decade many novel carbohydrate binding proteins (CBPs) have been described, and several have been documented to play critical roles in cell trafficking and cell signaling. Despite these advances, the rate of generating new information has been slow, and the biological roles of most mammalian CBPs remain poorly understood. While the importance of this field has attracted many outstanding laboratories, a major barrier to rapid progress has been the structural complexity and heterogeneity of the carbohydrates themselves, and the analytical and synthetic challenges this poses. A further complexity arises from the fact that carbohydrate ligands are post- translational modifications of proteins and lipids whose synthesis is directed by the coordinated expression of multiple genes in a manner that is not template driven.

protein complexes: To date scientists have studied proteins largely as discrete entities, yet most proteins operate collectively as part of protein complexes or pathways. A deeper understanding of protein interactions will assist in validating novel drug targets and may extend the usefulness of existing drug targets. At Cellzome we have implemented a high- throughput use of Tandem Affinity Purification (TAP) for effective isolation of complexes involved in human disease that is very robust, and is providing novel insights into cellular pathways.

protein-DNA interactions: Can be detected by DNA footprinting, gel shift analysis, yeast one hybrid assays or Southwestern blots.

protein dynamics: Certain parts of a particular protein will be rigid, but others may be flexible and change their shape, even when bound. ... NMR has the unique ability to characterize protein fluctuations quantitatively, much more so than crystallography can.Understanding the function of a protein is fundamental for gaining insight into many biological processes. Proteins are stable mechanical constructs that allow certain internal motions to enable their biological function. Structural properties of a protein can be obtained with X-ray crystallography or NMR acquisition techniques. Molecular dynamics (MD) simulations at pico/ nano- second time scales output one or more trajectory files which describe the coordinates of each individual atom over time. The main problem with animating these trajectories is one of temporal scale. Taking large time steps will destroy the impression of smooth motion, while small time steps will result in the camouflage of interesting motions.

protein function: More systematic attempts have been made to place proteins within a hierarchy of standard functional categories or to connect them in overlapping networks of varying types of associations. These networks can obviously include protein- protein interactions ... More broadly, they can include pathways, regulatory systems and signaling cascades... Perhaps, in the future, the systematic combination of networks may provide for a truly rigorous definition of protein function. A biologically useful definition of the function of a protein requires a description at several different levels. To the biochemist, function means the biochemical role of an individual protein: if it is an enzyme, function refers to the reaction catalyzed; if it is a signaling protein, function refers to the interactions that the protein makes. To the geneticist or cell biologist, function includes these roles but will also encompass the cellular roles of the protein, such as the phenotype of its deletion, the pathway in which it operates, among others. A physiologist or developmental biologist may have an even broader view of function, including tissue specificity and expression during the life cycle of the organism. In the expanded view of protein function, a protein is defined as an element in the network of its interactions. Various terms have been coined for this expanded notion of function, such as 'contextual function' or 'cellular function'. Whatever the term, the idea is that each protein in living matter functions as part of an extended web of interacting molecules. Often it is possible to understand the cellular functions of uncharacterized proteins through their linkages to characterized proteins. In broader terms, the networks of linkages offer a new view of the meaning of protein function, and in time should offer a deepened understanding of the function of cells.

protein identification: The analytical method used most commonly to visualize and identify large numbers of proteins is 2D-gel electrophoresis. One can theoretically visualize changes in protein production, both qualitatively and quantitatively, from two individual samples (e.g., a control preparation and a treated preparation). Furthermore, one can potentially accomplish protein identification by "picking" proteins from the 2D- gel and subjecting the highly purified protein to MALDI- TOF mass spectrometry.

protein informatics: Includes bioinformatics technology to cross reference protein informatics with genomic databases, sequence data of protein fragments by mass spectrometry and identification of these fragments using more remote relationships; construction and management of international protein structural databases; protein profiling and characterization data handling; data that elucidates the relationship between structures and functions of biological macromolecules by X-ray crystallography, large scale molecular simulation and structural bioinformatics, protein structure data handling and storage, structural bioinformatics covering molecular modeling and design; protein array and chip data handling; development of new algorithms and software for large scale simulation calculations by parallel computers; protein- protein interaction data and libraries; protein structure data determination by X-ray crystallography and development of automatic analysis systems; protein expression databases; automated technology for high- throughput protein function assignment and annotation. Although mining of protein structure homology data is a relatively small field now, it is likely to experience dramatic growth and to become pivotal in the ultimate exploitation of genomic data and tools.

protein interactions: Networks of protein interactions control the lives of cells, yet we are only beginning to appreciate the nature and complexity of these networks. We have taken two approaches to the study of protein networks. The first is to infer functional interactions between proteins from genome sequences and correlated mRNA expression. The second approach is to reconstruct networks from published experimental studies in the scientific literature. While proteomics is defined as a comprehensive study of proteins expressed by an organism, it is often limited to expression profiling and sequence analysis. In reality, of course, proteins are not important simply because they are present but because they have unique functions. Most proteins function at least partly through their interactions with other proteins, and this information is not apparent from 2D PAGE expression analysis or amino acid sequencing. A comprehensive analysis of protein interactions is thus critical to proteomics as functional analysis cannot otherwise be considered complete. Protein interactions may be studied via expression in yeast two- hybrid complementation systems. But the tremendous quantity of data necessary for comprehensive analysis requires utilization of modern automated sample- handling instrumentation and data- handling software. AxCell Biosciences has developed true high- throughput, in vitro protein interaction analysis. This process involves highly parallel peptide synthesis and protein expression, as well as custom HTS solutions. With InforMax, AxCell is also developing sophisticated tools for facile visualization and experimental manipulation of the complex patterns and pathways of protein interaction important for intracellular signaling processes.

protein knockouts: Our proteomics efforts are focused largely on developing new techniques to probe protein- protein interactions and to construct devices that allow one to monitor the levels and post- translational modification states of hundreds or even thousands of proteins simultaneously. A third major goal is to develop "protein knockout" methods that would allow researchers to rapidly develop reagents to block one or more functions of a newly discovered protein to facilitate studies of its role in cellular metabolism.

protein networks: Yeast two- hybrid screens have provided a wealth of information describing potential protein- protein interactions in cells. This talk will discuss large- scale two- hybrid screening in Saccharomyces cerevisiae using "living" protein arrays consisting of ordered grids of protein fusions that are expressed in growing yeast cells. Potential protein interactions identified from these screens can be compiled into graphical maps of protein networks. The development of other novel high- throughput technologies for assaying protein function will also be discussed.

protein- protein interactions: Correlated changes in protein expression (such as co- regulation or sequential regulation) provide a hint that two proteins may be interacting with each other. A central phenomenon determining the biological pathways found in living systems. They are the focus of many proteomic technologies being developed today to decipher an intricate network of interactions. Play a major role in almost all relevant physiological processes occurring in living organisms, including DNA replication and transcription, RNA splicing, protein biosynthesis, and signal transduction.

protein-RNA interactions: Can be detected by the yeast three- hybrid assay.

proteome: The scope note for the Journal of Proteome Research (Jan.2002) states that "primary topics will include: New approaches to sample preparation, including 2- D gels and chromatographic techniques, Advancements in high- throughput protein identification and analysis, Array- based measurements, Structural genomics data related to protein function, Research on quantitative and structural analysis of proteins and their post- translational modifications, Metabolic and signal pathway analysis, including metabolomics and peptidomics, Protein- protein, protein- DNA, and protein- small molecule interactions, Computational approaches to predict protein function, Use of Bioinformatics/ Cheminformatics to mine and analyze data, New tools in proteomic analysis, Studies on proteomics with an impact on the understanding of disease, diagnosis and medicine.

Comprehensive quantitative data on the proteins of an organism under a variety of conditions (ideally including post synthetic modifications and interactions with other molecules). To achieve this, purification each protein (including modified versions and interacting antibodies) will be an important related project The concept of the proteome is fundamentally different to that of the genome: while the genome is virtually static and can be well defined for an organism, the proteome continually changes in response to external and internal events.

proteome database mining: the identification of intrinsic patterns and relationships in translational expression data generated by large- scale proteomics experiments. Improvements in genome, gene expression and proteome database mining algorithms will enable the prediction of protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. Thus, the final objective of such higher- level functional analysis will be the elucidation of high-resolution structural and functional maps of the human genome. Proteome Informatics group is part of the Swiss Institute of Bioinformatics (SIB). It is in charge of research and development in the fields of bioinformatics, molecular imaging and the use of Internet for biomedical applications.

proteomic diversity: Alternative RNA splicing generates extreme proteomic diversity in the mammalian nervous system, where hundreds of thousands of distinct proteins are generated from approximately 30,000 genes. These protein counterparts play important roles in learning and memory, cell communication, and neural development.

proteomics: The analysis of complete complements of proteins. Proteomics includes not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, activities, and, ultimately, their function. Initially encompassing just two- dimensional (2D) gel electrophoresis for protein separation and identification, proteomics now refers to any procedure that characterizes large sets of proteins. The explosive growth of this field is driven by multiple forces - genomics and its revelation of more and more new proteins; powerful protein technologies, such as newly developed mass spectrometry approaches, global (yeast) two- hybrid techniques, and spin- offs from DNA arrays; and innovative computational tools and methods to process, analyze, and interpret prodigious amounts of data. Proteomics is the new "omics" on the block. This conference is designed to showcase protein- protein interactions, protein array production, protein profiling, and the resulting potential of protein research for drug discovery. Rarely acknowledged, economics is an important aspect of the "omics" family as well. Although proteomics does remain hypothesis- driven, advances in technologies such as chips, arrays, and informatics mean this burgeoning enterprise has the potential application to turn "omics" from red into green. In-depth coverage of the high- throughput protein expression analysis and characterization field, as well as its impact on diagnostic and therapeutic product development. At present, the aggregate of activities called proteomics has three distinct technical subsets: protein profiling, protein- protein interaction and structural biology. ... (producing) voluminous amounts of data ... substantial attention is now being applied to annotation methods by which the resulting information, e.g., source protein, types of modifications, subcellular organelle, cell expression profiles, known protein interaction, protein domain organization, atom- by- atom structural coordinates, etc. can be archived in a manner amenable by computer query and in silico cross references. The use of quantitative protein- level measurements of gene expression to characterize biological processes (e.g. disease processes and drug effects) and decipher the mechanisms of gene expression control. As such, proteomics focuses on the dynamic description of gene regulation and, by doing so, offers something much more powerful than a protein equivalent of DNA databases: the concept of molecular recognition as a systematic science. For this reason, proteomics emphasizes quantitation and the assembly of large bodies of experimental observations in numerical databases. Variant spellings without (as far as I can tell) truly variant meanings seem to distinguish proteinomics and proteonics. I would welcome any thoughts or comments on these words. Related term proteonomics.

proteomics - commercialization: Covers key areas in proteomics today, including new approaches to protein expression, evolving methods of studying protein function, new technologies such as protein chips, and advances in protein informatics. Focuses on how researchers are applying new proteomic approaches to drug discovery and development, and how these technologies can be used most effectively and in a high- throughput capacity. Case studies analyzing particular applications of proteomic technologies to specific disease- related research are provided, and future trends and developments are forecast.

proteomics technologies: For a field so laden with razzmatazz methods, it is striking that the number one need in proteomics may be new technology. There are simply not enough assays that are sufficiently streamlined to allow the automation necessary to perform them on a genome's worth of proteins. Those currently available barely scratch the surface of the thousands of specialized analyses biologists use every day on their favorite proteins. What we need are experimental strategies that could be termed cell biological genomics, biophysical genomics, physiological genomics, and so on, to provide clues to function. In addition, a protein contains so many types of information that each of its properties needs to be assayed on a proteome- wide scale, ideally in a quantitative manner. Although automation is being applied to what has traditionally been the workhorse of protein analysis - 2D gel electrophoresis - many limitations remain as to the speed, sensitivity and reproducibility of this decades old method.

proteonomics: Expression systems that can rapidly produce high levels of recombinant proteins are a critical link between the discovery of new genes and the identification of targets and molecules for drug development. Advances in the baculovirus expression technology makes it the system of choice in the emerging field of proteonomics where rapid production and high yields of biologically active complex proteins are essential in the discovery of new drug targets, vaccines, and biotherapeutics.

quantitation - proteins: A CD microlaboratory platform has been developed for quantification of multiple proteins in crude samples. A sandwich type of fluorescent assay has been implemented for multiple parallel analyses in CD utilizing discrete affinity capturing beds with different binding specificities corresponding to the analytes of interest. Aliquots of sample are processed in parallel by controlling flow rate over the affinity bed using centrifugal force. Bound proteins are further detected by sequential addition of complementary fluorescent ligand followed by in situ detection of fluorescence. Sub- nanomolar concentrations of serum proteins in 100-nl sample volumes have been accurately quantified in less than 15 minutes.

regulatory homology: Quantitative analysis of protein expression data obtained by high - throughput methods has led us to define the concept of "regulatory homology" and use it to begin to elucidate the basic structure of gene expression control in vivo.

reverse proteomics: In reverse proteomics, the starting point is the DNA sequence of the genome of an organism. First, the transcriptome (complete set of transcripts) and proteome (complete set of proteins) are predicted in silico and subsequently this information is used to generate reagents for their analysis. Compounds can be tested to see if they can disrupt protein - protein interactions - a strategy that may be extremely useful for the development of new drugs.

reverse-two hybrid: A variation of the yeast two hybrid system, in which protein- protein interactions increase the transcription of a toxic counterselectable marker, resulting in growth inhibition. The availability of a counterselectable marker significantly extends the possibilities of the two- hybrid system. Most importantly, dissociation of protein- protein interactions can be selected for, and thus protein- protein interactions can be characterized and manipulated genetically.

Rosetta stone method: A way of looking at the correlation of protein domains across species. Some proteins have homologs that are fused in other species, yielding clues as to the proteins with which they might interact. In addition, proteins that have been identified in particular complexes and pathways hint at the location and function of their homologs in other species.  Allows complete bypassing of 2D-gel electrophoresis. Resembles shotgun genome sequencing. Proteins are broken apart, then the peptides are sequenced, and reassembled. The process is made much easier by the sequencing of the human genome, and the more complete that sequence is, the stronger the approach is. Shotgun proteomics is enabled by multidimensional protein identification technology (MudPIT).

Tandem Affinity Purification TAP: A generic and rapid method being developed at EMBL to recover proteins that are present in the cell even at very low concentrations, utilizing a "TAP tag".

targeted proteomics: Biochemical approaches to proteomics, particularly using mass spectrometry.

tissue proteomics: The National Cancer Institute and the Food & Drug Administration are funding a multimillion dollar ''Tissue Proteomics Initiative'' to identify proteins linked to early stages of colon, breast, and other cancers.

topological proteomics: At the current stage of the life sciences industry, those companies with more efficient technologies for turning genomics and proteomics information into drug discovery programs will be the most successful companies. The number of new potential drug targets is overwhelming drug developers who need appropriate tools to better lead compounds for development. Efficient target validation will become a key driver of success. MelTec has developed a whole- cell protein fingerprinting technology capable of gathering the topological proteomics information of intact cells in their natural environment in tissues; visualizing protein networks and correlating them with cellular function. This accelerate and enhance the drug target and lead compound selection and validation processes.

toxicoproteomics: Study of global protein expression to better understand toxicology.

whole proteome: Proteome analysis has become indispensable and complementary to genomic analysis. With access to whole genome sequences from various organisms and with the imminent completion of many more, the SWISS- PROT group at EBI has developed a research- oriented initiative that utilizes many of the existing resources and provides comparative analysis of the predicted protein coding sequences of all complete genomes.

yeast one hybrid: Variation on yeast two hybrid system, used for detecting protein- DNA interactions.

yeast three hybrid: Modification of yeast two hybrid system. The third hybrid may be a first one with an RNA or with a small molecule that is a cell permeable chemical inducer of dimerization.

yeast two hybrid: An approach to studying protein- protein interactions. The basic format involves the creation of two hybrid molecules, one in which a "bait" protein is fused with a transcription factor, and one in which a "prey" protein is fused with a related transcription factor. If the bait and prey proteins indeed interact, then the two factors fused to these two proteins are also brought into proximity with each other. As a result, a specific signal is produced, indicating an interaction has taken place. A system first developed in 1989 (by Stan Fields and colleagues) to identify proteins (and their genes) that interact with known proteins.