bluuebunny/crossref_metadata_2025_split huggingface dataset:
An animal model of chronic inflammatory pain: Pharmacological and temporal differentiation from acute models
Authors: Wilson Alex W. , Medhurst Stephen J. , Dixon Claire I. , Bontoft Nick C. , Winyard Lisa A. , Brackenborough Kim T. , De Alba Jorge , Clarke Christopher J. , Gunthorpe Martin J. , Hicks Gareth A. , Bountra Chas , McQueen Daniel S. , Chessell Iain P. 
Published: October 2005

AbstractClinically, inflammatory pain is far more persistent than that typically modelled pre‐clinically, with the majority of animal models focussing on short‐term effects of the inflammatory pain response. The large attrition rate of compounds in the clinic which show pre‐clinical efficacy suggests the need for novel models of, or approaches to, chronic inflammatory pain if novel mechanisms are to make it to the market. A model in which a more chronic inflammatory hypersensitivity phenotype is profiled may allow for a more clinically predictive tool. The aims of these studies were to characterise and validate a chronic model of inflammatory pain. We have shown that injection of a large volume of adjuvant to the intra‐articular space of the rat knee results in a prolonged inflammatory pain response, compared to the response in an acute adjuvant model. Additionally, this model also results in a hypersensitive state in the presence and absence of inflammation. A range of clinically effective analgesics demonstrate activity in this chronic model, including morphine (3 mg/kg, t.i.d.), dexamethasone (1 mg/kg, b.i.d.), ibuprofen (30 mg/kg, t.i.d.), etoricoxib (5 mg/kg, b.i.d.) and rofecoxib (0.3–10 mg/kg, b.i.d.). A further aim was to exemplify the utility of this chronic model over the more acute intra‐plantar adjuvant model using two novel therapeutic approaches; NR2B selective NMDA receptor antagonism and iNOS inhibition. Our data shows that different effects were observed with these therapies when comparing the acute model with the model of chronic inflammatory joint pain. These data suggest that the chronic model may be more relevant to identifying mechanisms for the treatment of chronic inflammatory pain states in the clinic.
A Holocene Pollen and Diatom Record from Vanderlin Island, Gulf of Carpentaria, Lowland Tropical Australia
Authors: Prebble Matiu , Sim Robin , Finn Jan , Fink David 
Published: October 2005

AbstractSedimentary, palynological and diatom data from a dunefield lake deposit in the interior of Vanderlin Island in the Gulf of Carpentaria are presented. Prior to the formation of present perennial lake conditions, the intensified Australian monsoon associated with the early Holocene marine transgression allowed Cyperaceae sedges to colonise the alluvial margins of an expansive salt flat surrounded by an open Eucalyptus woodland. As sea level stabilised between 7500 and 4500 cal yr B.P. coastal dunes ceased to develop allowing dense Melaleuca forest to establish in a Restionaceae swamp. Dune-sand input into the swamp was diminished further as the increasingly dense vegetation prevented fluvial and aeolian transported sand arriving from coastal sources. This same process impounded the drainage basin allowing a perennial lake to form between 5500 and 4000 cal yr B.P. Myriophyllum and other aquatic taxa colonised the lake periphery under the most extensive woodland recorded for the Holocene. The palynological data support an effective precipitation model proposed for northern Australia that suggests more variable conditions in the late Holocene. A more precise measure of effective precipitation change is provided by diatom-based inferences that indicate few changes in lake hydrology. Such interpretations are explained in terms of palynological sensitivity to adjustments in local fire regimes where regional precipitation change may only be recorded indirectly through fire promoting mechanisms, including intensified ENSO periodicity and human impact.
Evidence that the plant cannabinoid Δ9‐tetrahydrocannabivarin is a cannabinoid CB1and CB2receptor antagonist
Authors: Thomas Adèle , Stevenson Lesley A , Wease Kerrie N , Price Martin R , Baillie Gemma , Ross Ruth A , Pertwee Roger G 
Published: October 2005

Δ9‐tetrahydrocannabivarin (THCV) displaced [3H]CP55940 from specific binding sites on mouse brain and CHO‐hCB2cell membranes (Ki=75.4 and 62.8 nM, respectively).THCV (1 μM) also antagonized CP55940‐induced stimulation of [35S]GTPγS binding to these membranes (apparentKB=93.1 and 10.1 nM, respectively).In the mouse vas deferens, the ability of Δ9‐tetrahydrocannabinol (THC) to inhibit electrically evoked contractions was antagonized by THCV, its apparentKB‐value (96.7 nM) approximating the apparentKB‐values for its antagonism of CP55940‐ andR‐(+)‐WIN55212‐induced stimulation of [35S]GTPγS binding to mouse brain membranes.THCV also antagonizedR‐(+)‐WIN55212, anandamide, methanandamide and CP55940 in the vas deferens, but with lower apparentKB‐values (1.5, 1.2, 4.6 and 10.3 nM, respectively).THCV (100 nM) did not oppose clonidine, capsaicin or (−)‐7‐hydroxy‐cannabidiol‐dimethylheptyl‐induced inhibition of electrically evoked contractions of the vas deferens.Contractile responses of the vas deferens to phenylephrine hydrochloride orβ,γ‐methylene‐ATP were not reduced by 1 μMTHCV orR‐(+)‐WIN55212, suggesting that THCV interacts withR‐(+)‐WIN55212 at prejunctional sites.At 32 μM, THCV did reduce contractile responses to phenylephrine hydrochloride andβ,γ‐methylene‐ATP, and above 3 μMit inhibited electrically evoked contractions of the vas deferens in an SR141716A‐independent manner.In conclusion, THCV behaves as a competitive CB1and CB2receptor antagonist. In the vas deferens, it antagonized several cannabinoids more potently than THC and was also more potent against CP55940 andR‐(+)‐WIN55212 in this tissue than in brain membranes. The bases of these agonist‐ and tissue‐dependent effects remain to be established.British Journal of Pharmacology(2005)146, 917–926. doi:10.1038/sj.bjp.0706414
SIMAP—The similarity matrix of proteins
Authors: Arnold Roland , Rattei Thomas , Tischler Patrick , Truong Minh-Duc , Stümpflen Volker , Mewes Werner 
Published: October 2005

Abstract
Motivation: Sequence similarity searches are of great importance in bioinformatics. Exhaustive searches for homologous proteins in databases are computationally expensive and can be replaced by a database of pre-calculated homologies in many cases. Retrieving similarities from an incrementally updated database instead of repeatedly recalculating them should provide homologs much faster and frees computational resources for other purposes.
Results: We have implemented SIMAP—a database containing the similarity space formed by almost all amino acid sequences from public databases and completely sequenced genomes. The database is capable of handling very large datasets and allows incremental updates. We have implemented a powerful backbone for similarity computation, which is based on FASTA heuristics. By providing WWW interfaces as well as web services, we make our data accessible to the worldwide community. We have also adapted procedures to detect putative orthologs as example applications.
Availability: The SIMAP portal page providing links to SIMAP services is publicly available: http://mips.gsf.de/services/analysis/simap/. The web services can be accessed under http://mips.gsf.de/proj/hobitws/services/RPCSimapService?wsdl and http://mips.gsf.de/proj/hobitws/services/DocSimapService?wsdl
Contact: t.rattei@wzw.tum.de
ARTS: alignment of RNA tertiary structures
Authors: Dror Oranit , Nussinov Ruth , Wolfson Haim 
Published: October 2005

Abstract
Motivation: A fast growing number of non-coding RNAs have recently been discovered to play essential roles in many cellular processes. Similar to proteins, understanding the functions of these active RNAs requires methods for analyzing their tertiary structures. However, in contrast to the wide range of structure-based approaches available for proteins, there is still a lack of methods for studying RNA structures.
Results: We present a new computational method named ARTS (alignment of RNA tertiary structures). The method compares two nucleic acid structures (RNAs or DNAs) and detects a-priori unknown common substructures. These substructures can be either large global folds containing hundreds and even thousands of nucleotides or small local tertiary motifs with at least two successive base pairs. To the best of our knowledge, this is the first method of this type. The method is highly-efficient and was used to conduct an all-against-all comparison of all the RNA structures currently available in the Protein Data Bank.
Availability: The program, a web-server and supplementary information are available on http://bioinfo3d.cs.tau.ac.il/ARTS
Contact: oranit@post.tau.ac.il
Non-coding RNAs in Ciona intestinalis
Authors: Missal Kristin , Rose Dominic , Stadler Peter F. 
Published: October 2005

Abstract
Motivation: The analysis of animal genomes showed that only a minute part of their DNA codes for proteins. Recent experimental results agree, however, that a large fraction of these genomes are transcribed and hence are probably functional at the RNA level. A computational survey of vertebrate genomes has predicted thousands of previously unknown ncRNAs with evolutionarily conserved secondary structures. Extending these comparative studies beyond vertebrates is difficult, however, since most ncRNAs evolve quickly at the sequence level while conserving their characteristic secondarystructures.
Results: We report on a computational screen of structured ncRNAs in the urochordate lineage based on a comparison of the genomic data from Ciona intestinalis, Ciona savignyi and Oikopleura dioica. We predict &gt;1000 ncRNAs with an evolutionarily conserved RNA secondary structure. Of these, about a quarter are located in introns of known protein coding sequences. A few RNA motifs can be identified as known RNAs, including ∼300 tRNAs, some 100 snRNA genes and a few microRNAs and snoRNAs.
Availability: www.bioinf.uni-leipzig.de/Publications/SUPPLEMENTS/05-008/
Contact: kristin@bioinf.uni-leipzig.de
Finding exact optimal motifs in matrix representation by partitioning
Authors: Leung Henry C. M. , Chin Francis Y. L. 
Published: October 2005

Abstract
Motivation: Finding common patterns, or motifs, in the promoter regions of co-expressed genes is an important problem in bioinformatics. A common representation of the motif is by probability matrix or PSSM (position specific scoring matrix). However, even for a motif of length six or seven, there is no algorithm that can guarantee finding the exact optimal matrix from an infinite number of possible matrices.
Results: This paper introduces the first algorithm, called EOMM, for finding the exact optimal matrix-represented motif, or simply optimal motif. Based on branch-and-bound searching by partitioning the solution space recursively, EOMM can find the optimal motif of size up to eight or nine, and a motif of larger size with any desired accuracy on the principle that the smaller the error bound, the longer the running time. Experiments show that for some real and simulated data sets, EOMM finds the motif despite very weak signals when existing software, such as MEME and MITRA-PSSM, fails to do so.
Availability:
Contact: cmleung2@cs.hku.hk
Analyzing microarray data using quantitative association rules
Authors: Georgii Elisabeth , Richter Lothar , Rückert Ulrich , Kramer Stefan 
Published: October 2005

Abstract
Motivation: We tackle the problem of finding regularities in microarray data. Various data mining tools, such as clustering, classification, Bayesian networks and association rules, have been applied so far to gain insight into gene-expression data. Association rule mining techniques used so far work on discretizations of the data and cannot account for cumulative effects. In this paper, we investigate the use of quantitative association rules that can operate directly on numeric data and represent cumulative effects of variables. Technically speaking, this type of quantitative association rules based on half-spaces can find non-axis-parallel regularities.
Results: We performed a variety of experiments testing the utility of quantitative association rules for microarray data. First of all, the results should be statistically significant and robust against fluctuations in the data. Next, the approach should be scalable in the number of variables, which is important for such high-dimensional data. Finally, the rules should make sense biologically and be sufficiently different from rules found in regular association rule mining working with discretizations. In all of these dimensions, the proposed approach performed satisfactorily. Therefore, quantitative association rules based on half-spaces should be considered as a tool for the analysis of microarray gene-expression data.
Availability: The code is available from the authors on request.
Contact: kramer@in.tum.de
Lineage-specific gene loss following mitochondrial endosymbiosis and its potential for function prediction in eukaryotes
Authors: Gabaldón Toni , Huynen Martijn A. 
Published: October 2005

Abstract
Motivation: The endosymbiotic origin of mitochondria has resulted in a massive horizontal transfer of genetic material from an alpha-proteobacterium to the early eukaryotes. Using large-scale phylogenetic analysis we have previously identified 630 orthologous groups of proteins derived from this event. Here we show that this proto-mitochondrial protein set has undergone extensive lineage-specific gene loss in the eukaryotes, with an average of three losses per orthologous group in a phylogeny of nine species. This gene loss has resulted in a high variability of the alphaproteobacterial-derived gene content of present-day eukaryotic genomes that might reflect functional adaptation to different environments. Proteins functioning in the same biochemical pathway tend to have a similar history of gene loss events, and we use this property to predict functional interactions among proteins in our set.
Contact: T.Gabaldon@cmbi.ru.nl
Supplementary information: Sequences and trees for the selected orthologous groups can be accessed at http://www.cmbi.kun.nl/~jagabald/table_groupsb.html
Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models
Authors: Husmeier Dirk 
Published: October 2005

Abstract
Motivation: A recently proposed method for detecting recombination in DNA sequence alignments is based on the combination of hidden Markov models (HMMs) with phylogenetic trees. Although this method was found to detect breakpoints of recombinant regions more accurately than most existing techniques, it inherently fails to distinguish between recombination and rate variation. In the present paper, we propose to marry the phylogenetic tree to a factorial HMM (FHMM). The states of the first hidden chain represent tree topologies, whereas the states of the second independent hidden chain represent different global scaling factors of the branch lengths. Inference is done in terms of a hierarchical Bayesian model, where parameters and hidden states are sampled from the posterior distribution with Gibbs sampling.
Results: We have tested the proposed model on various synthetic and real-world DNA sequence alignments. The simulation results suggest that as opposed to the standard phylogenetic HMM, the phylogenetic FHMM clearly distinguishes between recombination and rate heterogeneity and thereby avoids the prediction of spurious recombinant regions.
Availability: The proposed method has been implemented in a MATLAB package that extends Kevin Murphy's HMM toolbox. Software and data used in our study are available from http://www.bioss.sari.ac.uk/~dirk/Supplements
Contact: dirk@bioss.ac.uk
Recovering haplotype structure through recombination and gene conversion
Authors: Lajoie Mathieu , El-Mabrouk Nadia 
Published: October 2005

Abstract
Motivation: Understanding haplotype evolution subject to mutation, recombination and gene conversion is fundamental to understand genetic specificities of human populations and hereditary bases of complex disorders. The goal of this project is to develop new algorithmic tools assisting the reconstruction of historical relationships between haplotypes and the inference of haplotypes from genotypes.
Results: We present two new algorithms. The first one finds an optimal pathway of mutations, recombinations and gene conversions leading to a given haplotype of size m from a population of h haplotypes. It runs in time O(mhs2), where s is the maximum number of contiguous sites that can be exchanged in a single gene conversion. The second one finds an optimal pathway of mutations and recombinations leading to a given genotype, and runs in time O(mh2). Both algorithms are based on a penalty score model and use a dynamic programming approach. We apply the second one to the problem of inferring haplotypes from genotypes, and show how it can be used as an independent tool, or to improve the performance of existing methods.
Availability: The algorithms have been implemented in JAVA and are available on request.
Contact: mabrouk@iro.umontreal.ca
Knowledge-based framework for hypothesis formation in biochemical networks
Authors: Tran Nam , Baral Chitta , Nagaraj Vinay J. , Joshi Lokesh 
Published: October 2005

Abstract
Motivation: The current knowledge about biochemical networks is largely incomplete. Thus biologists constantly need to revise or extend existing knowledge. The revision and/or extension are first formulated as theoretical hypotheses, then verified experimentally. Recently, biological data have been produced in great volumes and in diverse formats. It is a major challenge for biologists to process these data to reason about hypotheses. Many computer-aided systems have been developed to assist biologists in undertaking this challenge. The majority of the systems help in finding ‘pattern’ in data and leave the reasoning to biologists. A few systems have tried to automate the reasoning process of hypothesis formation. These systems generate hypotheses from a knowledge base and given observations. A main drawback of these knowledge-based systems is the knowledge representation formalisms they use. These formalisms are mostly monotonic and are now known to be not quite suitable for knowledge representation, especially in dealing with the inherently incomplete knowledge about biochemical networks.
Results: We present a knowledge-based framework for hypothesis formation for biochemical networks. The framework has been implemented by extending BioSigNet-RR—a knowledge based system that supports elaboration-tolerant representation and non-monotonic reasoning. Features of the extended system are illustrated by a case study of the p53 signal network.
Availability: http://www.biosignet.org
Contact: namtran@asu.edu
Growing Bayesian network models of gene networks from seed genes
Authors: Peña J. M. , Björkegren J. , Tegnér J. 
Published: October 2005

Abstract
Motivation: For the last few years, Bayesian networks (BNs) have received increasing attention from the computational biology community as models of gene networks, though learning them from gene-expression data is problematic. Most gene-expression databases contain measurements for thousands of genes, but the existing algorithms for learning BNs from data do not scale to such high-dimensional databases. This means that the user has to decide in advance which genes are included in the learning process, typically no more than a few hundreds, and which genes are excluded from it. This is not a trivial decision. We propose an alternative approach to overcome this problem.
Results: We propose a new algorithm for learning BN models of gene networks from gene-expression data. Our algorithm receives a seed gene S and a positive integer R from the user, and returns a BN for the genes that depend on S such that less than R other genes mediate the dependency. Our algorithm grows the BN, which initially only contains S, by repeating the following step R + 1 times and, then, pruning some genes; find the parents and children of all the genes in the BN and add them to it. Intuitively, our algorithm provides the user with a window of radius R around S to look at the BN model of a gene network without having to exclude any gene in advance. We prove that our algorithm is correct under the faithfulness assumption. We evaluate our algorithm on simulated and biological data (Rosetta compendium) with satisfactory results.
Contact: jmp@ifm.liu.se
Reconsidering complete search algorithms for protein backbone NMR assignment
Authors: Vitek Olga , Bailey-Kellogg Chris , Craig Bruce , Kuliniewicz Paul , Vitek Jan 
Published: October 2005

Abstract
Motivation: Nuclear magnetic resonance (NMR) spectroscopy is widely used to determine and analyze protein structures. An essential step in NMR studies is determining the backbone resonance assignment, which maps individual atoms to experimentally measured resonance frequencies. Performing assignment is challenging owing to the noise and ambiguity in NMR spectra. Although automated procedures have been investigated, by-and-large they are still struggling to gain acceptance because of inherent limits in scalability and/or unacceptable levels of assignment error. To have confidence in the results, an algorithm should be complete, i.e. able to identify all solutions consistent with the data, including all arbitrary configurations of extra and missing peaks. The ensuing combinatorial explosion in the space of possible assignments has led to the perception that complete search is hopelessly inefficient and cannot scale to realistic datasets.
Results: This paper presents a complete branch-contract-and-bound search algorithm for backbone resonance assignment. The algorithm controls the search space by hierarchically agglomerating partial assignments and employing statistically sound pruning criteria. It considers all solutions consistent with the data, and uniformly treats all combinations of extra and missing data. We demonstrate our approach on experimental data from five proteins ranging in size from 70 to 154 residues. The algorithm assigns &gt;95% of the positions with &gt;98% accuracy. We also present results on simulated data from 259 proteins from the RefDB database, ranging in size from 25 to 257 residues. The median computation time for these cases is 1 min, and the assignment accuracy is &gt;99%. These results demonstrate that complete search not only has the advantage of guaranteeing fair treatment of all feasible solutions, but is efficient enough to be employed effectively inpractice.
Availability: The MBA2 software package is made available under an open-source software license. The datasets featured in the Results section can also be obtained from the contact author.
Contact: ovitek@stat.purdue.edu
Fast maximum-likelihood refinement of electron microscopy images
Authors: Scheres Sjors H.W. , Valle Mikel , Carazo José-María 
Published: October 2005

Abstract
Motivation: Maximum-likelihood (ML) image refinement is a promising candidate to improve attainable resolution limits in 3D-EM. However, its large CPU requirements may prohibit application to 3D-structure optimization.
Results: We speeded up ML image refinement by reducing its search space over the alignment parameters. Application of this reduced-search approach to a cryo-EM dataset yielded practically identical results as the original approach, but in approximately one day instead of one week of CPU.
Availability: This work has been implemented in the public domain package Xmipp. Documentation and download instructions may be found at: http://www.cnb.uam.es/~bioinfo
Contact: carazo@cnb.uam.es