bluuebunny/crossref_metadata_2025 huggingface dataset:
Tandem mass spectrometry database searching
Authors: Eng Jimmy K. , Martin Daniel B. , Aebersold Ruedi
Published: April 2005

Associated with the emergence of mass spectrometry–based proteomics analysis, a host of novel algorithms for tandem mass spectrometry database searching have been published. These tools apply a breadth of computational and statistical approaches to solving the problem of identifying peptides based on interpreting tandem mass spectra with the constraint of sequences present in publicly available protein, transcript, and genomic sequence database repositories. With increasing data volumes due to continuous advances in instrumentation, the need for tools that perform automated peptide identifications and validation of those identifications will be magnified. An overview of database search and postsearch validation tools is summarized.
Time‐of‐flight mass spectrometry
Authors: Cotter Robert J.
Published: April 2005

Time‐of‐flight (TOF) mass spectrometers have become the instruments of choice where high molecular masses must be measured. Pulsed extraction, orthogonal extraction, and reflectron designs have greatly improved mass resolution. In addition, hybrid and tandem instruments, such as quadrupole/TOF, ion trap/TOF, and TOF/TOF mass spectrometers now provide the opportunity for obtaining tandem mass spectra. Time‐of‐flight instruments are used in proteomics for determining the molecular weights of intact proteins, for accurate mass measurements of tryptic peptides (mass fingerprinting), for amino acid sequencing (sequence tags) and for determining the locations and structures of posttranslational modifications.
Tutorial on tandem mass spectrometry database searching
Authors: Eng Jimmy K.
Published: April 2005

Identifying peptides, and ultimately proteins, by searching sequence databases with tandem mass spectra of peptides is one of the most widely used proteomics techniques. The steps by which a user actually performs a search are fairly straightforward and are described in this article. Although this article goes through the identification process of searching a single tandem mass spectrum to identify a single peptide, most users will not usually selective search only one spectrum but would query the full set of tandem mass spectra acquired in an entire LC‐MS/MS run. The underlying steps and analysis considerations outlined here are relevant in either scenario.
Improvement of sequence coverage in peptide mass fingerprinting
Authors: Hjernø Karin , Roepstorff Peter
Published: April 2005

In order to fully characterize and understand the biological significance of a protein (in a proteomics study), it needs to be characterized with respect to the presence of splice variants, isoforms, and posttranslational processing/modification. This requires full coverage of the protein sequence including that of minor variants of the protein. However, protein identification is often based on sequence coverages as low as 10–20%, and search for the remaining peptides is frequently like the search for
the needle in the haystack
. Here we present some approaches, which may be helpful for increasing the sequence coverage in proteomics studies.
Handling membrane proteins
Authors: Goode Robert J. A. , Simpson Richard J.
Published: April 2005

Membrane proteins fulfill several vital roles, including cell adhesion, solute transport, and receptor functions. Despite these important biological functions, very little is known about the structure and expression of these proteins at the protein level due to their low abundance, inherent hydrophobicity, and variable posttranslational modifications. In order to overcome these obstacles, classical proteomic techniques have been adapted and several techniques have been developed, allowing characterization of elusive membrane proteins.
ICAT
and other labeling strategies for semiquantitative
LC
‐based expression profiling
Authors: Byrne Connie , Cagney Gerard
Published: April 2005

Comprehensive proteome analysis requires efficient, robust, and practical methods for the identification and quantification of all proteins in complex biological samples. Mass spectrometry is a well‐established protein identification tool and semiquantitative proteomics has traditionally been performed using two‐dimensional gel electrophoresis (2‐DE) coupled with mass spectrometry. However, other separation strategies based on liquid chromatography now complement 2‐DE as a central method for analysis of proteins in complex biological systems. In this review, we discuss the most promising methodological developments in this area with particular attention to their merits and limitations.
Image analysis
Authors: Dowsey Andrew W. , Dunn Michael J. , Yang Guang‐Zhong
Published: April 2005

Owing to the volume of data and its experimental geometric and expression uncertainties, quantitative analysis of 2D gel electrophoresis data with image processing and modeling is an actively pursued research topic. The results of this analysis include accurate protein quantification, p
I
and
M
r
estimation, and the extraction of differential expression between control and sample gels. Systematic errors such as current leakage and background inhomogeneities need to be corrected for, followed by the segmentation, modeling, and quantification of each protein spot. To establish spot correspondences between multiple gels, a number of image registration and spot matching techniques for correcting geometric distortion have been proposed. They have facilitated the detection and quantification of differential expression through the statistical analysis of outliers and bias field. For large‐scale analysis, classification and clustering techniques can be employed to uncover intrinsic trends and relationships in the protein spot patterns. This section provides a short review of the computational techniques used in the analysis of 2‐DE gels and examines the pitfalls of existing methods. Some of the key areas that need to be developed in the coming years are highlighted, especially those related to statistical expression analysis (SEA) based on multiple gel runs, and image mining techniques through the use of high‐throughput processing based on the Grid technology.
Detecting protein posttranslational modifications using small molecule probes and multiwavelength imaging devices
Authors: Patton Wayne F.
Published: April 2005

Though there are alternatives to polyacrylamide gel electrophoresis, such as solution‐phase capillary electrophoresis, multidimensional chromatography, and microfluidic separations, the simplicity, reliability, and ready accessibility of the polyacrylamide gel ensures that it will remain a vital tool in proteomics endeavors for the foreseeable future. Two‐dimensional gel electrophoresis (2‐DE) remains the single most powerful analytical tool in the proteomics arsenal for global analysis of protein posttranslational modifications. Recently, the capabilities of 2‐DE have been dramatically enhanced through the introduction of fluorescence‐ and chemiluminescence‐based detection technologies, as well as complementary advanced imaging instrumentation, that permit routine detection of protein modifications such as phosphorylation, glycosylation, and S‐nitrosylation. These detection reagents are also applicable to the analysis of subproteomes on simple one‐dimensional SDS‐polyacrylamide gels, permitting rapid, higher throughput screening of fractionated proteins for the identification of potentially interesting samples that may subsequently be evaluated in greater detail by 2‐DE. Small‐molecule probes and multiwavelength imaging devices together greatly extend the capacity of gel electrophoresis with respect to the investigation of proteome‐wide changes in protein posttranslational modification levels without resorting to the use of radiolabeling.
Real‐time measurements of protein dynamics
Authors: Concannon Caoimhín G. , Duessmann Heiko , Prehn Jochen H. M.
Published: April 2005

Undoubtedly, the advent of green fluorescent protein (GFP) technology has made great advancements into our understanding of how key cellular functions unfold. The ability to fluorescently tag a protein without perturbing its functioning is central to this and has allowed us to perform quantitative bioimaging of protein movements and concentrations within living cells. The challenge for the future is to further expand this technology with more sophisticated imaging equipment and improved fluorescent proteins with increased spectral variation, thus improving our current understanding of protein dynamics.
Arraying proteins and antibodies
Authors: Wilson David S. , Nock Steffen
Published: April 2005

Protein arrays (
see
Protein microarrays as an emerging tool for proteomics
and
Protein arrays
) enable investigators to characterize multiple proteins in parallel while expending minimal amounts of precious biological samples. The individual features of arrays can be either arranged in a two‐dimensional grid on a planar surface, or they can be constructed from optically encoded particles suspended in a solution. A variety of substrates, chemistries, and arraying methods have been described. The choice among these methods should be made according to the nature of the application and the types and numbers of proteins that need to be arrayed.
Investigating protein–protein interactions in multisubunit proteins: the case of eukaryotic
RNA
polymerases
Authors: Guglielmi Benjamin , Zaros Cécile , Thuriaux Pierre , Werner Michel
Published: April 2005

The physiological functions executed by eukaryotic cells are often catalyzed by large multiprotein complexes. Very few complexes have been analyzed at a detailed structural level, and one therefore strongly relies on generic but indirect methods to establish protein–protein interaction maps between the polypeptide subunits of these complexes, and to delineate the relevant interacting domains. Currently, the two more popular approaches are based on protein “pull‐down” assays, where the ability of two partner polypeptides is measured by fast copurification tests, and by two‐hybrid interaction mapping, where interacting proteins reconstitute a functional heterodimeric transcriptional activator in vivo. If carefully implemented, both provide important insight into the organization of multiprotein complexes. The predictive power of these approaches will be assessed at the light of our current knowledge of eukaryotic DNA‐dependent RNA polymerases.
Functional classification of proteins based on protein interaction data
Authors: Brun Christine , Baudot Anaïs , Jacq Bernard
Published: April 2005

Deciphering gene/protein function for a better understanding of cell functioning and organism development is one of the main goals in biology. For this purpose, approaches have been designed following both methodological progress and thinking advancement. In this respect, computational methods played a constant role over time, evolving with the way biologists were apprehending gene/protein function. After a brief review of the more prominent bioinformatics methods and their implication in understanding gene/protein function, this article aims at explaining the importance of analyzing the protein–protein network with regard to the new vision of the cell functioning that it provides. In this respect, PRODISTIN, a computational method permitting the functional classification of proteins based on the analysis of the interaction network is presented along with the main conclusions it allowed us to reach.
FRET
‐based reporters for intracellular enzyme activity
Authors: Sato Moritoshi , Umezawa Yoshio
Published: April 2005

Fluorescence imaging is the most powerful technique available for observing spatial and temporal dynamics of ions and molecules in the single living cells. However, almost all the molecular events, including those involving second messengers and protein phosphorylation, are analyzed by conventional destructive methods, such as radio immunoassay and immunoblotting of cell lysates prepared from millions of cells. Here, we describe fluorescent reporters for protein phosphorylation and lipid second messengers that we recently developed, and show how their spatial and temporal dynamics can be monitored in single living cells. The present fluorescent reporters should be an indispensable tool not only for understanding the complex mechanism of the signal transduction in single cells and organisms but also for high‐throughput screening of pharmaceutical candidates that regulate the cellular extent of protein phosphorylation and lipid second messengers.
siRNAapproaches in cell biology
Authors: Gampel Alexandra , Mellor Harry
Published: April 2005

The success of the genome sequencing projects has given us access to the genetic identities of a wide range of organisms. Clearly, the greatest challenge now is to make use of this wealth of information and, specifically, to associate genes with physiological functions. In one of the bizarre coincidences that litter the history of scientific research, this challenge has emerged at the same time as a powerful new technique that seems ideally suited to the job in hand.
Quantitative image analysis and the Open Microscopy Environment
Authors: Swedlow Jason R. , Allan Chris , Falconi Andrea , Burel Jean‐Marie
Published: April 2005

Many advances have been made in instrumentation and image analysis algorithms for light microscope, yet computational cell biology remains out of reach for many investigators. The use of proprietary file formats by commercial software complicates the storage, analysis, and querying of image data. Integration of new algorithms into proprietary packages is difficult at best, and there are inadequate standards for sharing image data and results with colleagues. We have developed an open‐source software framework to address these limitations called the Open Microscopy Environment (
http://openmicroscopy.org
). The foundation of our system is a data model that is specifically designed for five‐dimensional microscope images (X, Y, Z, wavelengths, and time). This model is instantiated as an XML file that serves as a convenient data migration format for biological imaging. In addition, the OME Data Model is used to build an OME database and associated interfaces that serve as an integrated data storage, management, and analysis tool. The database stores all information regarding acquisition and all subsequent results from processing, analysis, and measurement. Using standard software interfaces, this design removes barriers of communication between different proprietary software packages. The Data Model, and by extension, the OME XML File and the OME database can be adapted to the requirements of local facilities. Finally, the system provides Web‐based and stand‐alone clients applications for visualizing image data and analytic results. OME is an open‐source software project, and OME code is licensed under the Less GNU General Public License. The latest documentation for OME and software releases are at
http://openmicroscopy.org
.
Structure/function of

N

‐glycans
Authors: Dwek Miriam V. , Brooks Susan
Published: April 2005

The posttranslational modification of proteins with N‐linked glycans is a topic of intense research as the N‐linked glycans attached to proteins have been found to have a profound effect on both structure and function of many glycoproteins. This article describes the biosynthesis and function of a range of proteins that are glycosylated with N‐linked oligosaccharides.
O‐linkedN‐acetylglucosamine (O‐GlcNAc)
Authors: Whelan Stephen A. , Hart Gerald W.
Published: April 2005

O‐linked β‐N‐acetylglucosamine (O‐GlcNAc) is an abundant and dynamic posttranslational modification that occurs on serine and threonine residues in functionally diverse nucleocytoplasmic proteins in all metazoans.O‐GlcNAc has been characterized to have functional roles in a number of disease states, as a nutrient sensor, in protein–protein interactions, and protein degradation. The regulation of these cellular functions, as well as many other potential functions, is studied through the use and development of proteomic techniques. IdentifyingO‐GlcNAc sites, in conjunction with other posttranslational modifications, will continue to play an essential role toward elucidating the complex regulation of proteins and the control on the cellular state.
Posttranslational cleavage of cell‐surface receptors
Authors: Stacey Martin , Davies John , Gordon Siamon , Lin Hsi‐Hsien
Published: April 2005

Nascent polypeptides generated by eukaryotes rarely represent the true form of mature proteins. Instead, many newly synthesized proteins undergo posttranslational modifications that may mediate either subtle or profound effects on the function of the protein. In this review, we focus on proteolytic cleavage as a type of irreversible posttranslational modification. We describe the different proteolytic mechanisms of three disparate families of cell‐surface receptors; Notch receptors, protease‐activated receptors (PARs) and G‐protein receptor proteolytic site (GPS) containing receptors. All of these exemplify how posttranslational modification by proteolysis can greatly affect receptor function through a variety of intriguing mechanisms.
Metalloproteins
Authors: Degtyarenko Kirill
Published: April 2005

Blood is red in vertebrates and blue in molluscs thanks to protein–metal complexes. Metalloproteins are involved in all fundamental biochemical processes including respiration, oxygenic photosynthesis, regulation of transcription and translation, nitrogen fixation, and metabolism of xenobiotics. Metalloenzymes were the first biological catalysts on Earth. Later, when the composition of the Earth's atmosphere changed dramatically due to photosynthesis, the metalloproteins evolved to counter the toxic effects of oxygen and harness it for new physiological functions. Currently, over one‐half of all proteins are estimated to bind metals. This article introduces but a small number of metalloprotein families, with emphasis on oxidoreductases, electron‐transfer proteins, and photosynthetic complexes.
Structure comparison and protein structure classifications
Authors: Redfern Oliver , Bennett Christopher , Orengo Christine
Published: April 2005

As genes duplicate and mutate over the course of evolution, their sequences can diverge beyond recognition. However, the three‐dimensional structures of these homologous proteins often remain conserved. When the number of solved structures in the Protein Databank (PDB) rose significantly in the early 1990s, it became possible to group these evolutionary relatives into protein families. Over time, this has given rise to comprehensive hierarchical databases of protein structures, such as CATH and SCOP, which rely on a combination of manual expert classification and structural comparison methods. There are over 50 of the latter algorithms, ranging from secondary structure fold comparison methods (GRATH, SSM) to more computationally intensive fragment and residue‐based approaches, such as DALI, CE, and SSAP. This chapter reviews the most popular methods and how they are combined with sequence comparison to recognize protein homologs. Many protein family databases (CATH, SCOP) focus on structural domains, rather than on whole polypeptide chains, so we examine approaches to automatic domain boundary assignment algorithms in parallel with the construction of protein structure classifications.
The
CATH
domain structure database
Authors: Pearl Frances , Bennett Christopher , Orengo Christine
Published: April 2005

The CATH database of protein domain structures (
http://www.biochem.ucl.ac.uk/bsm/cath/
) currently contains 60 435 domain structures classified into 917 fold groups, 1606 superfamilies, and 5202 sequence families. Recent developments include improved methods for rapidly recognizing domain boundaries in multidomain proteins. These exploit the principle of domain recurrence during evolution. Algorithms have been developed that identify these regions using a fast method that compares secondary structure arrangements between proteins (CATHEDRAL). In a recent CATH release, 75% of protein chains from the Protein Data Bank (PDB), with no significant sequence similarity to entries in CATH, had domains that could be recognized using this approach. Since domain boundary assignment is a significant bottleneck in the classification of new structures, CATHEDRAL will also help increase the frequency of CATH updates. CATH has recently been used to provide structural annotations for completed genomes. The Web‐based Gene3D resource assigns complete and partial genome sequences, from 120 completed genomes, to CATH domain structure superfamilies.
The importance of protein structural dynamics and the contribution of NMR spectroscopy
Authors: Kalverda Arnout P. , Thompson Gary S. , Bruce Turnbull W.
Published: April 2005

Dynamic motions in proteins facilitate many biochemical phenomena, for example, catalysis and allostery. Nuclear Magnetic Resonance (NMR) spectroscopy allows measurement of protein dynamics over a wide range of timescales.
NMR
Authors: Craven C. Jeremy
Published: April 2005

This article presents a brief introduction to NMR of proteins, followed by a consideration of the ways in which NMR can be used to screen proteins for structure determination projects by both NMR and X‐ray crystallography. Finally the current impact of NMR on structural proteomics projects is reviewed.
Electron microscopy as a tool for 3
D
structure determination in molecular structural biology
Authors: Ranson Neil A.
Published: April 2005

Electron microscopy (EM) is a method for determining the structure of large biological assemblies that are difficult targets for X‐ray crystallography. The fundamental properties and limitations of image formation in EM are described, along with the basic methods for obtaining and analyzing EM data that are currently in use.
Functional inference from probabilistic protein interaction networks
Authors: Bader Joel S.
Published: April 2005

The ability to obtain complete genome sequence for human and model organisms has shifted the grand challenge of genomics to describing the functional units of a genome and their interactions at the systems level. Protein‐coding genes are the dominant class of functional units, and protein–protein interactions provide the framework for understanding manifold biological processes. Recent years have seen exponential growth in the quantity of protein–protein interaction data available for inferring protein networks. Inference remains challenging, however, because of high false‐positive and false‐negative rates in the high‐throughput studies generating the majority of protein interaction data. Experimental studies now report confidence metrics together with interaction data, and similar methods have been applied retrospectively to analyze legacy data sets. Thus, a convenient level of abstraction for protein interaction data is a weighted graph in which vertices represent proteins, perhaps labeled by biological function, and edge weights represent confidence scores or likelihoods for pairwise interactions. Graph‐based models permit intuitive inference of protein function based on the function of neighboring proteins. This review provides a critical view of recent advances in algorithms for protein functional inference from probabilistic protein interaction networks. The types of algorithms considered, in order of increasing statistical rigor and computational cost, include nearest‐neighbor approaches, adaptive neighborhoods and tree‐building methods, energy minimization by simulated annealing and free energy minimization by message passing methods, and stochastic methods based on Gibbs sampling. The review explores the trade‐off between computational cost, predictive accuracy, and generalization error.
Reverse engineering gene regulatory networks
Authors: Thompson Michael J. , Driscoll Michael E. , Gardner Timothy S. , Collins James J.
Published: April 2005

Complex networks of genes, proteins, and small molecules interact to determine cellular function. The reverse engineering or inference of gene regulatory networks using DNA sequence data, protein–DNA binding data, and observed molecular abundance data has become a major interest of the biological community. We discuss recent successes and remaining challenges in the construction of gene network models and their use for gaining biological insight. We draw lessons from the detailed discussion of several recent gene network inference studies, focusing on the novel advances and limitations of each approach. These approaches differ in the strategies used to incorporate biological data, the level of physical detail and type of model used, and the purpose of the modeling in terms of biological discovery. The approaches we discuss aim to gain insights into the logic of combinatorial regulation occurring at a gene promoter, the activity of regulatory factors distinct from their abundance, the identification of key regulators in a gene network, and the prediction of drug compound mode of action. We suggest possibilities for future directions in network inference studies.
Analyzing and reconstructing gene regulatory networks
Authors: Rice J. Jeremy , Kershenbaum Aaron , Stolovitzky Gustavo
Published: April 2005

The study of networks is becoming an increasingly important area of biological research. This chapter starts with a general discussion of network properties, and then focuses on the transcriptional control network of
Escherichia coli
, a gene regulatory network that is better characterized than in most other organisms. This network is analyzed in terms of distinct layers that show short paths from higher, input to lower, output levels. This structure suggests that short temporal delays are favored over additional information integration that might be achieved with more levels of processing. Repeating structures, termed
motifs
, were discovered including triangle‐, square‐, and tree‐shaped motifs. In an example shown, discovered motifs suggest that functional modules may be inferred from such topological analyses. Other topological structures such as redundant pathways and negative feedback loops are not found, perhaps indicating that simple feed‐forward designs are favored over more complex systems that might improve cellular robustness. Current gene regulatory networks are reconstructed by combining data from many experiments and many labs using hypothesis‐driven approaches, but there is a growing effort to infer biological networks from high‐throughput and genome‐wide data sets. While sufficient data is generally lacking for fully detailed kinetic reconstructions, efforts to reconstruct network topology have shown promise. We review some of these reconstruction methods in light of an eventual goal of reconstructing whole regulatory networks.
Searching for genes and biologically related signals inDNAsequences
Authors: Pertea Mihaela
Published: April 2005

A key component of the most successful gene‐finding algorithms is the ability to recognize the DNA and RNA sequence patterns that characterize the biological signals that are critical for transcription, splicing, and translation. This chapter discusses some of the most commonly predicted of these signals and the methods that are usually used for their detection. Unfortunately, there is no completely accurate method to identify any of these patterns, although increasingly complex computational techniques have been developed.
Gene structure prediction in plant genomes
Authors: Brendel Volker
Published: April 2005

Following the completion of the
Arabidopsis
genome sequence, other plant genome sequences are rapidly accumulating. Computational gene structure annotation in these sequences is a pressing and challenging task. Current approaches are discussed, including ab initio methods, cDNA/EST spliced alignment, and protein spliced alignment. Best results are achieved with combined methods, and human expert annotation will remain necessary to achieve high reliability in large‐scale annotation efforts.
Alternative splicing in humans
Authors: Conboy John G. , Dubchak Inna
Published: April 2005

Alternative pre‐mRNA splicing is the mechanism by which a cell fine‐tunes gene expression, by deciding what discrete segments of a gene's total coding information should be selected for expression in a specific cell type. The phenomenon of multiple alternative splicing pathways in the human genome, and the opportunity to regulate these pathways during development, allows a relatively small number of genes to encode a complex proteome in tissue‐specific patterns. Individual splicing decisions are controlled by interplay among splicing regulatory proteins, acting at specific enhancer and silencer sequences in the pre‐mRNA, and the catalytic machinery known as the spliceosome. Proper splicing regulation is a critical aspect of gene expression during normal human development, and derangements in this process are responsible for many human diseases. Recent advances in genome sequencing, gene expression profiling, bioinformatics, and biochemical analysis of the splicing machinery give hope that the rules by which splicing regulatory networks govern alternative splicing in humans will be deduced.
Dynamic programming for gene finders
Authors: Majoros William H.
Published: April 2005

Dynamic programming (DP) is a common algorithmic technique for the efficient evaluation of recurrence relations. Owing to the combinatorial nature of the gene prediction problem and the resulting recursive formulations that are typically adopted for modeling gene structure, the effective use of dynamic programming is particularly crucial to the implementation of a successful gene finder. This article considers the major complicating aspects of the technique, such as banding, numerical underflow, memory management, validation, and the use of heuristics to achieve an acceptable space/time trade‐off.
Phylogenetic profiling
Authors: Pellegrini Matteo , Fitz‐Gibbon Sorel T. , Yeates Todd O. , Eisenberg David
Published: April 2005

Phylogenetic profiling involves the study of the occurrence of gene families across fully sequenced genomes. For any gene, it is possible to create a phylogenetic profile, which encodes the presence or absence of homologs of the gene across organisms. Phylogenetic profiles may be used to measure the evolutionary distance between organisms, leading to the reconstruction of phylogenetic trees. The pairwise comparison of phylogenetic profiles allows us to identify genes that co‐occur across organisms and are likely to participate within the same pathway or protein complex. Finally, by comparing phylogenetic profiles to phenotypic profiles that encode the presence or absence of phenotypes across organisms, it is possible to infer that a gene is partially responsible for establishing a phenotype. These techniques are currently used to survey about 100 fully sequenced genomes that are currently determined. However, they promise to become more informative as the number of fully sequenced genomes increases by orders of magnitude.
Mass spectrometric data mining for protein sequences
Authors: Cole Christian , Lester Patrick J. , Hubbard Simon J.
Published: April 2005

The identification of proteins from characteristic mass spectra underpins much of proteome science, using various experimental and bioinformatic strategies to match the analytical data to protein sequences in the databases. Typically, this relies on bioinformatic approaches that are able to reconcile mass spectrometric data with possible peptide sequences, either in a database or
de novo
, in order to identify the protein(s) under study. A variety of bioinformatic search tools are available for this, using a range of approaches to search, score, and assess the significance of potential matches. These approaches are reviewed in this article and placed into the context of modern proteomics, including potential future developments and directions in which the field is moving.
Secondary structure prediction
Authors: Tan Ching Wai , Jones David T.
Published: April 2005

The problem of predicting protein secondary structure from amino acid is briefly reviewed. The discussion covers the problem of defining secondary structure, the basis of modern prediction methods, and finally, the problem of how predictions can be evaluated. Modern methods are found to be between 74 and 80% accurate (per‐residue) for 3‐state (helix/strand/coil) prediction, and it is becoming evident that further improvements in accuracy will only come from considering the aspects of the tertiary structure of proteins.
Modeling tertiary structure of
RNA
Authors: Masquida Benoît , Westhof Eric
Published: April 2005

A computer‐based approach to the modeling of the architecture of RNA molecules is described. It exploits the available crystal structures, sequences, and analyzing tools. The method is anchored in our understanding of the physicochemical processes that RNA molecules undergo when folding into their three‐dimensional structures. The folding is sequential, with modular units being incorporated hierarchically in the final architecture. The aim is to assemble a folded architecture of a structured RNA from known modules and known interaction motifs in order to suggest further experimental work about new contacts or new folding units. Although large RNA molecules are built using all‐atom components, the atomic details cannot, in most regions, be deduced with confidence.
Introduction to ontologies in biomedicine: from powertools to assistants
Authors: Altman Russ B.
Published: April 2005

Computer science is a complex discipline, but at its core can be summarized as the study of two interrelated concepts: algorithms and data structures. Data structures organize information to enable algorithms to work effectively. Because algorithms seem to “do the work”, data structures are often described as secondary accessories to effective algorithms. However, in many situations, an appropriate data structure allows the associated algorithms to be very simple or even trivial. Ontologies are data structures that represent knowledge, and so can be called “knowledge structures” (Schulze‐Kremer,

). They have received attention recently as a critical component of the computational infrastructure of biomedicine. This section of the encyclopedia is devoted to reviewing the state of the art of ontology construction and use. In this introduction, I place this work in the larger picture of biomedical computation.
Integrated bioinformatics software at
NCBI
Authors: Ferre Fabrizio
Published: April 2005

The National Center for Biotechnology Information (NCBI) provides a number of tools important in the bioinformatics analysis of proteins, nucleic acid sequences, genes, and their biological significance. The user is allowed to start at the whole‐genome level and reach the protein three‐dimensional structural detail level. Links and software integration permit an easy flow of information between different resources. This review will focus on all those tools that are not related to the detection of homology (
see
Detecting protein homology using NCBI tools
).
Design ofKEGGandGO
Authors: Kanehisa Minoru
Published: April 2005

The complete genome sequence contains the information about a repertoire of genes, which would enable the understanding of higher‐level complexity of cellular functions and organismic phenotypes. The process of genome annotation, in which individual gene functions are assigned, should then be coupled with capturing collective features of higher‐level biological systems. The two resources, KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology), provide facilities for computational mapping of individual gene functions to higher‐level systemic functions with different concepts and implementations.
Using the
P
ython programming language for bioinformatics
Authors: Sanner Michel F.
Published: April 2005

Molecular biology is evolving from the study of macromolecules in isolation toward complex environments, potentially as large as complete cells. The amount and heterogeneity of information that needs to be processed and integrated in order to understand and simulate such complexity requires a leap in the level of sophistication of our software tools. In this article, we describe the advantages of interpretive languages in general and Python in particular, over compiled languages for tackling this formidable software engineering and integration problem.
Brief
P
ython tutorial for bioinformatics
Authors: Poidinger Michael
Published: April 2005

Python is an interpreted, interactive, object‐orientated programming language in widespread use. This article summarizes the syntax of the Python programming language, and with examples demonstrates how the language can be used to perform biological data analyses and implement bioinformatic applications.
Amplifiers in RF Transceiver for Wireless Communication
Authors: Heo Deukhyoun , Upadhyaya Parag , Rajashekharaiah Mallesh
Published: April 2005

Wireless communication entails transmission and reception of data with air and surrounding environment as a communication channel. The channel, in this case the surrounding environment, therefore, dictates the quality of wireless communication. Wireless communication uses radio frequency (RF) as carrier frequency for data transmission and reception. The channel for RF communication (surrounding environment) is lossy, and thus, it is necessary to boost or amplify the signal levels during both transmission and reception. In the transmitter, the power amplifier (PA) is used to boost the signal power levels, and at the receiver, the low noise amplifier (LNA) is used to amplify the weak RF signals. The power amplifier and the low noise amplifier, consequently, dictate the quality of wireless or RF communication and therefore are critical in RF transceiver design.
Antenna Reverberation Chamber
Authors: Kouveliotis N.K. , Trakadas P.T. , Heretakis I.I. , Capsalis C.N.
Published: April 2005

The use of the reverberation chamber for performing electromagnetic compatibility (EMC) tests and antenna measurements is examined in this article. This kind of chamber exhibits a significant number of advantages compared to the other commonly used test sites. Its low cost, compact, and easily built structure simultaneously appears to host a very “convenient” electromagnetic environment inside the enclosure, with regard to the requirements that are posted by the standard that is followed during the EMC or any other type of test such as antenna measurements. More specifically, antenna radiation efficiency measurements prove to be satisfactorily performed through the use of a reverberating enclosure, as well as other antenna parameters (e.g., input impedance) tests. The basic characteristics of such a structure are presented with regard to the recently introduced IEC 61000‐4‐21 specification and studies available in the literature. The field uniformity requirements are being extensively described, as well as ways of improving the achieved uniformity. The field inside a reverberating enclosure is statistically characterized with the use of the models proposed in the literature, which are experimentally verified. The use of the reverberation chamber at relatively low frequencies is presented, together with its ability to store large amounts of energy. Finally, the different ways of operating a reverberation chamber are described with regard to which of its features is (are) needed for each instance. The whole presentation marks out the usefulness of the reverberation chamber for performing electromagnetic compatibility tests as well as antenna measurements.
Boundary‐Value Problems
Authors: Beker Benjamin , Cokkinides George , Jin Kong Myung
Published: April 2005

This article strictly concentrates on the use of the finite‐difference method (FDM) in the numerical analysis of boundary value problems associated with primarily static and to some extent quasistatic electromagnetic (EM) fields. Although all examples presented herein deal with EM‐related engineering applications, some numerical aspects of FDM are also covered.

The emphasis will be placed on the applications of FDM to three‐dimensional boundary value problems involving objects with arbitrary geometric shapes that are composed of complex dielectric materials.
Applied Numerical Electromagnetic Analysis for Planar High Frequency Circuits
Authors: Rautio James C.
Published: April 2005

Numerical electromagnetics entered mainstream high frequency and microwave design starting about 1990. Today, with much faster computers and more powerful algorithms and design flows, numerical electromagnetics is now considered as required in nearly all high‐frequency design. This article discusses the impact of numerical electromagnetics on design of planar circuits at high frequency, including silicon and gallium arsenide integrated radiofrequency integrated circuits (RFIC), and low temperature cofired ceramic (LTCC) circuits.
Coplanar Waveguide Components
Authors: Simons Rainee N.
Published: April 2005

Hybrid couplers and magic TS form the basic building blocks of balanced amplifiers, up/downconverters, frequency multipliers, and feed network of printed‐circuit antennas. The manufacturing of these components will be tremendously simplified if they are realized using uniplanar transmission lines such as coplanar waveguides. This article presents the design considerations for reduced‐size uniplanar hybrid coupler, magic‐T, and aperture‐coupled printed antennas.
Electromagnetic Ferrite Tile Absorber
Authors: Holloway Christopher L. , Baker–Jarvis James R. , Johnk Robert T. , Geyer Richard G.
Published: April 2005

In this chapter, we discuss the ferrite tile, ferrite grids, and hybrid combinations of urethane and ferrite absorbers typically used in electromagnetic test chambers for the 30MHz to 1000MHz frequency range. We present formulas and calculated reflectivities (or reflection coefficients). We also discuss how material properties and reflectivities are measured for the ferrite‐tile absorbers.
Electromagnetic Modeling
Authors: Vahldieck R. , Hoefer Wolfgang J.R.
Published: April 2005

Numerical modeling of electromagnetic (EM) fields or computational electromagnetics is a combination of numerical methods and field theory.

This article will focus only on some mainstream techniques, most of which employ either the method of weighted residuals or variational principles.We will begin with modeling techniques in the frequency domain, most importantly the method of moments (MoM). This section is followed by time‐domain methods and here in particular the finite‐difference time‐domain method (FDTD) and the transmission‐line matrix (TLM) method. Finally, a brief overview with respect to hybrid methods concludes this article. A comparison between the various modeling approaches as well as their advantages and disadvantages is added where appropriate.
Fast Fourier Transforms and Nufft
Authors: Liu Qing Huo
Published: April 2005

The fast Fourier transform (FFT) algorithm is one of most fundamental and powerful computational tools in computational science and engineering. In this article, the development of the fast Fourier transform algorithm is reviewed, some representative applications in electromagnetics are illustrated, and some recent developments in extending the FFT algorithms to nonuniformly sampled data and to discontinuous functions are summarized.
Feedforward Amplifiers
Authors: Gardner P.
Published: April 2005

A feedforward amplifier is a transmitter subsystem in which feedforward linearization is used to correct for the effects of nonlinearities in the gain and phase response of a basic amplifier.

Such nonlinearities have the effect of generating intermodulation products in multicarrier systems, and spectral regrowth in systems that use bandlimited, nonconstant envelope modulation. Odd‐order intermodulation is a particular problem in communication systems because it can generate spurious signals very close in frequency to the wanted signals, often in adjacent communication channels. Similarly, spectral regrowth is a problem because it generates unwanted noise or crosstalk in adjacent frequency bands, violating the tough out‐of‐band emissions specifications imposed by modern communication standards. The problems can be reduced, in principle, by the use of separate amplifiers for each channel, and/or linear class A amplifiers backed off well below saturation, but these measures make transmitters highly inefficient.

A better compromise between efficiency and linearity can be achieved by using artificial linearization techniques. This article describes one such technique: feedforward linearization. The basic principle of operation is described, the practical limitations are discussed, and comparisons with other linearization techniques are also made. Some advanced techniques are also introduced, including dual‐loop feedforward amplifiers and adaptive feedforward.
Ferrite Loaded Waveguides
Authors: Marqués Ricardo
Published: April 2005

This article describes the main physical effects due to the propagation and guidance of electromagnetic waves in ferrite‐loaded waveguides useful in microwave technology. The linear approach, in which the high‐frequency magnetic susceptibility of the ferrite is a function susceptibility of the ferrite is a function static magnetic field, will be considered valid. This approach includes the analysis of exchange free electromagnetic waves, as well as magnetostatic waves approximations, but not the analysis of spin waves nonlinear effects, magnetoelastic waves, and other complex interactions.
Enhancements of the Finite Difference Time Domain Method
Authors: Mittra Raj , Yu Wenhua , Chen Yinchao
Published: April 2005

There are two major challenging issues encountered in using the conventional finite‐difference time‐domain (FDTD) methods for solving electromagnetic field problems, namely, reducing the errors introduced by the staircasing approximation used to model objects with curved surfaces, and the dispersion effects when the number of cells per wavelength is not sufficiently large. In the first part of this article, we describe a conformal FDTD scheme that mitigates the staircasing error, regardless of whether we are dealing with PEC or dielectric objects. Next, we go on to discuss the multiresolution time‐domain (MRTD) method for the purpose of reducing the dispersive error introduced by large cell sizes in the conventional FDTD scheme. Several representative examples are employed to validate both of the proposed techniques.
Finite‐Difference Time‐Domain Analysis
Authors: Taflove Allen , Hagness Susan C.
Published: April 2005

The finite‐difference time‐domain (FDTD ) solution of Maxwell's equations is a robust and popular computational technique in science and engineering for modeling electromagnetic wave interactions with complex material structures. This article reviews key elements of the foundation of FDTD analysis as well as selected recent and emerging FDTD application areas.
Finlines
Authors: Hoefer Wolfgang J. R. , Vahldieck Ruediger
Published: April 2005

Finlines are guiding structures for electromagnetic waves that consist of one or several metallic fins suspended in theEplane of a waveguide enclosure. They are the basic transmission media for the so‐called integratedE‐plane circuit technology.

Finlines are applied predominantly in the frequency range between 10 and 100 GHz; but some applications at frequencies up to 170GHz have been realized. Having losses of typically 0.1 dB per wavelength, finlines are not suitable for long‐distance transmission. However, they excel as a circuit medium for millimeter‐wave components and systems due to their low manufacturing cost, wide single‐mode bandwidth, compatibility with discrete active and passive devices, and suitability for integration with other hybrid circuit techniques as well as with standard rectangular waveguides.