bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure comparison and protein structure classifications
Authors: Redfern Oliver , Bennett Christopher , Orengo Christine 
Published: April 2005

Abstract
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

Abstract

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

Abstract
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.
Electron microscopy as a tool for 3
D
structure determination in molecular structural biology
Authors: Ranson Neil A. 
Published: April 2005

Abstract
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

Abstract
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

Abstract
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

Abstract

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

AbstractA 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

Abstract

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

AbstractAlternative 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

AbstractDynamic 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

AbstractPhylogenetic 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

Abstract

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

Abstract
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

Abstract
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

Abstract

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

Abstract

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

AbstractThe 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

Abstract
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.
Amplifiers in RF Transceiver for Wireless Communication
Authors: Heo Deukhyoun , Upadhyaya Parag , Rajashekharaiah Mallesh 
Published: April 2005

AbstractWireless 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

AbstractThe 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

AbstractThis 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

AbstractNumerical 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

AbstractHybrid 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

AbstractIn 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.