bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Chado case study: an ontology-based modular schema for representing genome-associated biological information
Authors: Mungall Christopher J. , Emmert David B. ,   The FlyBase Consortium
Published: July 2007

Abstract
Motivation: A few years ago, FlyBase undertook to design a new database schema to store Drosophila data. It would fully integrate genomic sequence and annotation data with bibliographic, genetic, phenotypic and molecular data from the literature representing a distillation of the first 100 years of research on this major animal model system. In developing this new integrated schema, FlyBase also made a commitment to ensure that its design was generic, extensible and available as open source, so that it could be employed as the core schema of any model organism data repository, thereby avoiding redundant software development and potentially increasing interoperability. Our question was whether we could create a relational database schema that would be successfully reused.
Results: Chado is a relational database schema now being used to manage biological knowledge for a wide variety of organisms, from human to pathogens, especially the classes of information that directly or indirectly can be associated with genome sequences or the primary RNA and protein products encoded by a genome. Biological databases that conform to this schema can interoperate with one another, and with application software from the Generic Model Organism Database (GMOD) toolkit. Chado is distinctive because its design is driven by ontologies. The use of ontologies (or controlled vocabularies) is ubiquitous across the schema, as they are used as a means of typing entities. The Chado schema is partitioned into integrated subschemas (modules), each encapsulating a different biological domain, and each described using representations in appropriate ontologies. To illustrate this methodology, we describe here the Chado modules used for describing genomic sequences.
Availability: GMOD is a collaboration of several model organism database groups, including FlyBase, to develop a set of open-source software for managing model organism data. The Chado schema is freely distributed under the terms of the Artistic License (http://www.opensource.org/licenses/artistic-license.php) from GMOD (www.gmod.org).
Contact: cjm@fruitfly.org or emmert@morgan.harvard.edu.
Automatic genome-wide reconstruction of phylogenetic gene trees
Authors: Wapinski Ilan , Pfeffer Avi , Friedman Nir , Regev Aviv 
Published: July 2007

Abstract
Gene duplication and divergence is a major evolutionary force. Despite the growing number of fully sequenced genomes, methods for investigating these events on a genome-wide scale are still in their infancy. Here, we present SYNERGY, a novel and scalable algorithm that uses sequence similarity and a given species phylogeny to reconstruct the underlying evolutionary history of all genes in a large group of species. In doing so, SYNERGY resolves homology relations and accurately distinguishes orthologs from paralogs. We applied our approach to a set of nine fully sequenced fungal genomes spanning 150 million years, generating a genome-wide catalog of orthologous groups and corresponding gene trees. Our results are highly accurate when compared to a manually curated gold standard, and are robust to the quality of input according to a novel jackknife confidence scoring. The reconstructed gene trees provide a comprehensive view of gene evolution on a genomic scale. Our approach can be applied to any set of sequenced eukaryotic species with a known phylogeny, and opens the way to systematic studies of the evolution of individual genes, molecular systems and whole genomes.
Contact: aregev@broad.mit.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Identification of new drug classification terms in textual resources
Authors: Kolářik Corinna , Hofmann-Apitius Martin , Zimmermann Marc , Fluck Juliane 
Published: July 2007

Abstract
Knowledge about biological effects of small molecules helps in the understanding of biological processes and supports the development of new therapeutic agents. DrugBank is a high quality database providing such information about drugs that contains annotation of drug effects and classification of therapeutic effects. However, to broaden the scope of such a database in classifying and annotating drugs, systems for automatic extraction of classification terms and the corresponding annotation of drugs are needed. We have developed an approach for the identification of new terms used in unstructured text that provide information about drug properties. It is based on the identification and extraction of phrases corresponding to lexico-syntactic patterns - so-called Hearst patterns that contain drug names and directly related drug annotation terms. Such phrases could be identified with a high performance in DrugBank text (0.89 F-score) and in Medline abstracts (0.83 F-score). In comparison to DrugBank annotation terminology, a huge amount of new drug annotation terms could be found. The evaluation of terms extracted from Medline showed that 29–53% of them are new valid drug property terms. They could be assigned to existing and new drug property classes not provided by the DrugBank drug annotation. We come to the conclusion that our system can support database content update by providing additionally drug descriptions of pharmacological effects not yet found in databases like DrugBank. Moreover, we propose that automatic normalization of terms improves the annotation and the retrieval of relevant database entries.
Contact: corinna.kolarik@scai.fraunhofer.de
Supplementary information: Supplementary data are available at Bioinformatics online.
Dead-End Elimination with Backbone Flexibility
Authors: Georgiev Ivelin , Donald Bruce R. 
Published: July 2007

Abstract
Motivation: Dead-End Elimination (DEE) is a powerful algorithm capable of reducing the search space for structure-based protein design by a combinatorial factor. By using a fixed backbone template, a rotamer library, and a potential energy function, DEE identifies and prunes rotamer choices that are provably not part of the Global Minimum Energy Conformation (GMEC), effectively eliminating the majority of the conformations that must be subsequently enumerated to obtain the GMEC. Since a fixed-backbone model biases the algorithm predictions against protein sequences for which even small backbone movements may result in a significantly enhanced stability, the incorporation of backbone flexibility can improve the accuracy of the design predictions. If explicit backbone flexibility is incorporated into the model, however, the traditional DEE criteria can no longer guarantee that the flexible-backbone GMEC, the lowest-energy conformation when the backbone is allowed to flex, will not be pruned.
Results: We derive a novel DEE pruning criterion, flexible-backbone DEE (BD), that is provably accurate with backbone flexibility, guaranteeing that no rotamers belonging to the flexible-backbone GMEC are pruned; we also present further enhancements to BD for improved pruning efficiency. The results from applying our novel algorithms to redesign the β1 domain of protein G and to switch the substrate specificity of the NRPS enzyme GrsA-PheA are then compared against the results from previous fixed-backbone DEE algorithms. We confirm experimentally that traditional-DEE is indeed not provably-accurate with backbone flexibility and that BD is capable of generating conformations with significantly lower energies, thus confirming the feasibility of our novel algorithms.
Availability: Contact authors for source code.
Contact: brd+ismb07@cs.duke.edu
Supervised reconstruction of biological networks with local models
Authors: Bleakley Kevin , Biau Gérard , Vert Jean-Philippe 
Published: July 2007

Abstract
Motivation: Inference and reconstruction of biological networks from heterogeneous data is currently an active research subject with several important applications in systems biology. The problem has been attacked from many different points of view with varying degrees of success. In particular, predicting new edges with a reasonable false discovery rate is highly demanded for practical applications, but remains extremely challenging due to the sparsity of the networks of interest.
Results: While most previous approaches based on the partial knowledge of the network to be inferred build global models to predict new edges over the network, we introduce here a novel method which predicts whether there is an edge from a newly added vertex to each of the vertices of a known network using local models. This involves learning individually a certain subnetwork associated with each vertex of the known network, then using the discovered classification rule associated with only that vertex to predict the edge to the new vertex. Excellent experimental results are shown in the case of metabolic and protein–protein interaction network reconstruction from a variety of genomic data.
Availability: An implementation of the proposed algorithm is available upon request from the authors.
Contact: Jean-Philippe.Vert@ensmp.fr
Computational modeling of Caenorhabditis elegans vulval induction
Authors: Sun Xiaoyun , Hong Pengyu 
Published: July 2007

Abstract
Motivation: Caenorhabditis elegans vulval development is a paradigmatic example of animal organogenesis with extensive experimental data. During vulval induction, each of the six multipotent vulval precursor cells (VPCs) commits to one of three fates (1°, 2°, 3°). The precise 1°-2°-3° formation of VPC fates is controlled by a network of intercellular signaling, intracellular signal transduction and transcriptional regulation. The construction of mathematical models for this network will enable hypothesis generation, biological mechanism discovery and system behavior analysis.
Results: We have developed a mathematical model based on dynamic Bayesian networks to model the biological network that governs the VPC 1°-2°-3° pattern formation process. Our model has six interconnected subnetworks corresponding to six VPCs. Each VPC subnetwork contains 20 components. The causal relationships among network components are quantitatively encoded in the structure and parameters of the model. Statistical machine learning techniques were developed to automatically learn both the structure and parameters of the model from data collected from literatures. The learned model is capable of simulating vulval induction under 36 different genetic conditions. Our model also contains a few hypothetical causal relationships between network components, and hence can serve as guidance for designing future experiments. The statistical learning nature of our methodology makes it easy to not only handle noise in data but also automatically incorporate new experimental data to refine the model.
Contact: hong@cs.brandeis.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Homology search for genes
Authors: Cui Xuefeng , Vinař Tomáš , Brejová Broňa , Shasha Dennis , Li Ming 
Published: July 2007

Abstract
Motivation: Life science researchers often require an exhaustive list of protein coding genes similar to a given query gene. To find such genes, homology search tools, such as BLAST or PatternHunter, return a set of high-scoring pairs (HSPs). These HSPs then need to be correlated with existing sequence annotations, or assembled manually into putative gene structures. This process is error-prone and labor-intensive, especially in genomes without reliable gene annotation.
Results: We have developed a homology search solution that automates this process, and instead of HSPs returns complete gene structures. We achieve better sensitivity and specificity by adapting a hidden Markov model for gene finding to reflect features of the query gene. Compared to traditional homology search, our novel approach identifies splice sites much more reliably and can even locate exons that were lost in the query gene.
On a testing set of 400 mouse query genes, we report 79% exon sensitivity and 80% exon specificity in the human genome based on orthologous genes annotated in NCBI HomoloGene. In the same set, we also found 50 (12%) gene structures with better protein alignment scores than the ones identified in HomoloGene.
Availability: The Java implementation is available for download from http://www.bioinformatics.uwaterloo.ca/software
Contact: mli@uwaterloo.ca
GSEA-P: a desktop application for Gene Set Enrichment Analysis
Authors: Subramanian Aravind , Kuehn Heidi , Gould Joshua , Tamayo Pablo , Mesirov Jill P. 
Published: July 2007

AbstractGene Set Enrichment Analysis (GSEA) is a computational method that assesses whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states. We report the availability of a new version of the Java based software (GSEA-P 2.0) that represents a major improvement on the previous release through the addition of a leading edge analysis component, seamless integration with the Molecular Signature Database (MSigDB) and an embedded browser that allows users to search for gene sets and map them to a variety of microarray platform formats. This functionality makes it possible for users to directly import gene sets from MSigDB for analysis with GSEA. We have also improved the visualizations in GSEA-P 2.0 and added links to a new form of concise gene set annotations called Gene Set Cards. These additions, as well as other improvements suggested by over 3500 users who have downloaded the software over the past year have been incorporated into this new release of the GSEA-P Java desktop program.Availability: GSEA-P 2.0 is freely available for academic and commercial users and can be downloaded from http://www.broad.mit.edu/GSEAContact: mesirov@broad.mit.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Exploring biological network structure using exponential random graph models
Authors: Saul Zachary M. , Filkov Vladimir 
Published: July 2007

AbstractMotivation: The functioning of biological networks depends in large part on their complex underlying structure. When studying their systemic nature many modeling approaches focus on identifying simple, but prominent, structural components, as such components are easier to understand, and, once identified, can be used as building blocks to succinctly describe the network.Results: In recent social network studies, exponential random graph models have been used extensively to model global social network structure as a function of their ‘local features’. Starting from those studies, we describe the exponential random graph models and demonstrate their utility in modeling the architecture of biological networks as a function of the prominence of local features. We argue that the flexibility, in terms of the number of available local feature choices, and scalability, in terms of the network sizes, make this approach ideal for statistical modeling of biological networks. We illustrate the modeling on both genetic and metabolic networks and provide a novel way of classifying biological networks based on the prevalence of their local features.Contact: saul@cs.ucdavis.edu
Escape ring selectivity, bycatch, and discard survivability in the New England fishery for deep-water red crab, Chaceon quinquedens
Authors: Tallack S. M. L. 
Published: July 2007

Abstract
Tallack, S. M. L. 2007. Escape ring selectivity, bycatch, and discard survivability in the New England fishery for deep-water red crab, Chaceon quinquedens. – ICES Journal of Marine Science, 64: 1579–1586. The trap fishery for red crab, Chaceon quinquedens, occurs at depths of 600–800 m along the continental slope of New England. The target product is a male crab with a carapace width of ∼105 mm or greater. Selectivity was tested at two discrete depths (600 and 800 m), for four different escape ring scenarios: control trap with no escape rings, and escape rings with internal diameters of 9, 10, and 11 cm. Proportions of non-marketable C. quinquedens were large (71–100%) at both depths for all traps, but were smallest in traps with escape rings. Discard mortality was estimated at ∼5% through caging experiments across three haul frequency conditions (every 24 h, every 4 d, and after 8 d), which represented the likely reality of multiple recaptures during a commercial trip. The impact of discarding techniques (low and high impact) was also assessed. If discard proportion estimates of >71% are realistic, and if an estimated ∼5% of these discards die, the recommendation must be made for fishery participants to improve gear selectivity, and thereby to minimize discard mortality rates. On the management side, stock assessments will be more accurate if estimates of discard mortality are incorporated.
Enzymatic Properties and Subcellular Localization of Arabidopsis β-N-Acetylhexosaminidases
Authors: Strasser Richard , Bondili Jayakumar Singh , Schoberer Jennifer , Svoboda Barbara , Liebminger Eva , Glössl Josef , Altmann Friedrich , Steinkellner Herta , Mach Lukas 
Published: July 2007

Abstract
Plant glycoproteins contain substantial amounts of paucimannosidic N-glycans lacking terminal GlcNAc residues at their nonreducing ends. It has been proposed that this is due to the action of β-hexosaminidases during late stages of N-glycan processing or in the course of N-glycan turnover. We have now cloned the three putative β-hexosaminidase sequences present in the Arabidopsis (Arabidopsis thaliana) genome. When heterologously expressed as soluble forms in Spodoptera frugiperda cells, the enzymes (termed HEXO1–3) could all hydrolyze the synthetic substrates p-nitrophenyl-2-acetamido-2-deoxy-β-d-glucopyranoside, p-nitrophenyl-2-acetamido-2-deoxy-β-d-galactopyranoside, 4-methylumbelliferyl-2-acetamido-2-deoxy-β-d-glucopyranoside, and 4-methylumbelliferyl-6-sulfo-2-acetamido-2-deoxy-β-d-glucopyranoside, albeit to a varying extent. HEXO1 to HEXO3 were further able to degrade pyridylaminated chitotriose, whereas pyridylaminated chitobiose was only cleaved by HEXO1. With N-glycan substrates, HEXO1 displayed a much higher specific activity than HEXO2 and HEXO3. Nevertheless, all three enzymes were capable of removing terminal GlcNAc residues from the α1,3- and α1,6-mannosyl branches of biantennary N-glycans without any strict branch preference. Subcellular localization studies with HEXO-fluorescent protein fusions transiently expressed in Nicotiana benthamiana plants showed that HEXO1 is a vacuolar protein. In contrast, HEXO2 and HEXO3 are mainly located at the plasma membrane. These results indicate that HEXO1 participates in N-glycan trimming in the vacuole, whereas HEXO2 and/or HEXO3 could be responsible for the processing of N-glycans present on secretory glycoproteins.
RTE1 Is a Golgi-Associated and ETR1-Dependent Negative Regulator of Ethylene Responses
Authors: Zhou Xin , Liu Qian , Xie Fang , Wen Chi-Kuang 
Published: July 2007

Abstract
Arabidopsis (Arabidopsis thaliana) RTE1 encodes a membrane protein and negatively regulates ethylene responses. Genetic and transformation studies suggest that the function of the wild-type RTE1 is primarily dependent on ETR1 and can be independent on the other receptors. Ethylene insensitivity caused by the overexpression of RTE1 is largely masked by the etr1-7 mutation, but not by any other receptor mutations. The wild-type ETR1 N terminus is sufficient to the activation of the RTE1 function and the ectopic expression of etr1(1–349) restored ethylene insensitivity conferred by 35S∷gRTE1 in etr1-7. The RTE1 N terminus is not essential to the etr1-2 function and the expression of rte1(NΔ49), which has an N-terminal deletion of 49 amino acid residues, restored ethylene insensitivity in etr1-2 rte1-2. The ectopic expression of GREEN FLUORESCENT PROTEIN (GFP)-RTE1 conferred ethylene insensitivity in wild type and the GFP fusion displayed fast movement within the cytoplasm. The GFP-RTE1 and EYFP-NAG proteins colocalized and the Brefeldin A treatment caused aggregation of GFP-RTE1, suggesting RTE1 is a Golgi-associated protein. Our results suggest specificity of the RTE1 function to ETR1 and that endomembranes may play a role in the ethylene signal transduction.
Molecular Interactions of a Soluble Gibberellin Receptor, GID1, with a Rice DELLA Protein, SLR1, and Gibberellin
Authors: Ueguchi-Tanaka Miyako , Nakajima Masatoshi , Katoh Etsuko , Ohmiya Hiroko , Asano Kenji , Saji Shoko , Hongyu Xiang , Ashikari Motoyuki , Kitano Hidemi , Yamaguchi Isomaro , Matsuoka Makoto 
Published: July 2007

Abstract
GIBBERELLIN INSENSITIVE DWARF1 (GID1) encodes a soluble gibberellin (GA) receptor that shares sequence similarity with a hormone-sensitive lipase (HSL). Previously, a yeast two-hybrid (Y2H) assay revealed that the GID1-GA complex directly interacts with SLENDER RICE1 (SLR1), a DELLA repressor protein in GA signaling. Here, we demonstrated, by pull-down and bimolecular fluorescence complementation (BiFC) experiments, that the GA-dependent GID1–SLR1 interaction also occurs in planta. GA4 was found to have the highest affinity to GID1 in Y2H assays and is the most effective form of GA in planta. Domain analyses of SLR1 using Y2H, gel filtration, and BiFC methods revealed that the DELLA and TVHYNP domains of SLR1 are required for the GID1–SLR1 interaction. To identify the important regions of GID1 for GA and SLR1 interactions, we used many different mutant versions of GID1, such as the spontaneous mutant GID1s, N- and C-terminal truncated GID1s, and mutagenized GID1 proteins with conserved amino acids replaced with Ala. The amino acid residues important for SLR1 interaction completely overlapped the residues required for GA binding that were scattered throughout the GID1 molecule. When we plotted these residues on the GID1 structure predicted by analogy with HSL tertiary structure, many residues were located at regions corresponding to the substrate binding pocket and lid. Furthermore, the GA–GID1 interaction was stabilized by SLR1. Based on these observations, we proposed a molecular model for interaction between GA, GID1, and SLR1.
Functional Analysis of the Epidermal-Specific MYB GenesCAPRICEandWEREWOLFinArabidopsis
Authors: Tominaga Rumi , Iwata Mineko , Okada Kiyotaka , Wada Takuji 
Published: July 2007

AbstractEpidermis cell differentiation in Arabidopsis thaliana is a model system for understanding the developmental end state of plant cells. Two types of MYB transcription factors, R2R3-MYB and R3-MYB, are involved in cell fate determination. To examine the molecular basis of this process, we analyzed the functional relationship of the R2R3-type MYB gene WEREWOLF (WER) and the R3-type MYB gene CAPRICE (CPC). Chimeric constructs made from the R3 MYB regions of WER and CPC used in reciprocal complementation experiments showed that the CPC R3 region cannot functionally substitute for the WER R3 region in the differentiation of hairless cells. However, WER R3 can substantially substitute for CPC R3. There are no differences in yeast interaction assays of WER or WER chimera proteins with GLABRA3 (GL3) or ENHANCER OF GLABRA3 (EGL3). CPC and CPC chimera proteins also have similar activity in preventing GL3 WER and EGL3 WER interactions. Furthermore, we showed by gel mobility shift assays that WER chimera proteins do not bind to the GL2 promoter region. However, a CPC chimera protein, which harbors the WER R3 motif, still binds to the GL2 promoter region.