Multi-source and ontology-based retrieval engine for maize mutant phenotypes

Model Organism Databases, including the various plant genome databases, collect and enable access to massive amounts of heterogeneous information, including sequence data, gene product information, images of mutant phenotypes, etc, as well as textual descriptions of many of these entities. While a variety of basic browsing and search capabilities are available to allow researchers to query and peruse the names and attributes of phenotypic data, next-generation search mechanisms that allow querying and ranking of text descriptions are much less common. In addition, the plant community needs an innovative way to leverage the existing links in these databases to search groups of text descriptions simultaneously. Furthermore, though much time and effort have been afforded to the development of plant-related ontologies, the knowledge embedded in these ontologies remains largely unused in available plant search mechanisms. Addressing these issues, we have developed a unique search engine for mutant phenotypes from MaizeGDB. This advanced search mechanism integrates various text description sources in MaizeGDB to aid a user in retrieving desired mutant phenotype information. Currently, descriptions of mutant phenotypes, loci and gene products are utilized collectively for each search, though expansion of the search mechanism to include other sources is straightforward. The retrieval engine, to our knowledge, is the first engine to exploit the content and structure of available domain ontologies, currently the Plant and Gene Ontologies, to expand and enrich retrieval results in major plant genomic databases

ProteinDBS v2.0: a web server for global and local protein structure search

ProteinDBS v2.0 is a web server designed for efficient and accurate comparisons and searches of structurally similar proteins from a large-scale database. It provides two comparison methods, global-to-global and local-to-local, to facilitate the searches of protein structures or substructures. ProteinDBS v2.0 applies advanced feature extraction algorithms and scalable indexing techniques to achieve a high-running speed while preserving reasonably high precision of structural comparison. The experimental results show that our system is able to return results of global comparisons in seconds from a complete Protein Data Bank (PDB) database of 152 959 protein chains and that it takes much less time to complete local comparisons from a non-redundant database of 3276 proteins than other accurate comparison methods. ProteinDBS v2.0 supports query by PDB protein ID and by new structures uploaded by users. To our knowledge, this is the only search engine that can simultaneously support global and local comparisons. ProteinDBS v2.0 is a useful tool to investigate functional or evolutional relationships among proteins. Moreover, the common substructures identified by local comparison can be potentially used to assist the human curation process in discovering new domains or folds from the ever-growing protein structure databases. The system is hosted at http://ProteinDBS.rnet.missouri.edu

A framework for automatic semantic video annotation

The rapidly increasing quantity of publicly available videos has driven research into developing automatic tools for indexing, rating, searching and retrieval. Textual semantic representations, such as tagging, labelling and annotation, are often important factors in the process of indexing any video, because of their user-friendly way of representing the semantics appropriate for search and retrieval. Ideally, this annotation should be inspired by the human cognitive way of perceiving and of describing videos. The difference between the low-level visual contents and the corresponding human perception is referred to as the ‘semantic gap’. Tackling this gap is even harder in the case of unconstrained videos, mainly due to the lack of any previous information about the analyzed video on the one hand, and the huge amount of generic knowledge required on the other. This paper introduces a framework for the Automatic Semantic Annotation of unconstrained videos. The proposed framework utilizes two non-domain-specific layers: low-level visual similarity matching, and an annotation analysis that employs commonsense knowledgebases. Commonsense ontology is created by incorporating multiple-structured semantic relationships. Experiments and black-box tests are carried out on standard video databases for action recognition and video information retrieval. White-box tests examine the performance of the individual intermediate layers of the framework, and the evaluation of the results and the statistical analysis show that integrating visual similarity matching with commonsense semantic relationships provides an effective approach to automated video annotation

Designing electronic collaborative learning environments

Electronic collaborative learning environments for learning and working are in vogue. Designers design them according to their own constructivist interpretations of what collaborative learning is and what it should achieve. Educators employ them with different educational approaches and in diverse situations to achieve different ends. Students use them, sometimes very enthusiastically, but often in a perfunctory way. Finally, researchers study them and—as is usually the case when apples and oranges are compared—find no conclusive evidence as to whether or not they work, where they do or do not work, when they do or do not work and, most importantly, why, they do or do not work. This contribution presents an affordance framework for such collaborative learning environments; an interaction design procedure for designing, developing, and implementing them; and an educational affordance approach to the use of tasks in those environments. It also presents the results of three projects dealing with these three issues

BRISC—An Open Source Pulmonary Nodule Image Retrieval Framework

We have created a content-based image retrieval framework for computed tomography images of pulmonary nodules. When presented with a nodule image, the system retrieves images of similar nodules from a collection prepared by the Lung Image Database Consortium (LIDC). The system (1) extracts images of individual nodules from the LIDC collection based on LIDC expert annotations, (2) stores the extracted data in a flat XML database, (3) calculates a set of quantitative descriptors for each nodule that provide a high-level characterization of its texture, and (4) uses various measures to determine the similarity of two nodules and perform queries on a selected query nodule. Using our framework, we compared three feature extraction methods: Haralick co-occurrence, Gabor filters, and Markov random fields. Gabor and Markov descriptors perform better at retrieving similar nodules than do Haralick co-occurrence techniques, with best retrieval precisions in excess of 88%. Because the software we have developed and the reference images are both open source and publicly available they may be incorporated into both commercial and academic imaging workstations and extended by others in their research

DOMMINO: a database of macromolecular interactions

With the growing number of experimentally resolved structures of macromolecular complexes, it becomes clear that the interactions that involve protein structures are mediated not only by the protein domains, but also by various non-structured regions, such as interdomain linkers, or terminal sequences. Here, we present DOMMINO (http://dommino.org), a comprehensive database of macromolecular interactions that includes the interactions between protein domains, interdomain linkers, N- and C-terminal regions and protein peptides. The database complements SCOP domain annotations with domain predictions by SUPERFAMILY and is automatically updated every week. The database interface is designed to provide the user with a three-stage pipeline to study macromolecular interactions: (i) a flexible search that can include a PDB ID, type of interaction, SCOP family of interacting proteins, organism name, interaction keyword and a minimal threshold on the number of contact pairs; (ii) visualization of subunit interaction network, where the user can investigate the types of interactions within a macromolecular assembly; and (iii) visualization of an interface structure between any pair of the interacting subunits, where the user can highlight several different types of residues within the interfaces as well as study the structure of the corresponding binary complex of subunits

Spinal antinociception mediated by a cocaine-sensitive dopaminergic supraspinal mechanism

The role of dopaminergic descending supraspinal processes in mediating the antinociceptive action of cocaine was studied in the rat using a combination of extracellular neuronal recording and behavioral techniques. Neurons in the superficial laminae (I-II) of the spinal dorsal horn with receptive fields on the tail were recorded in anesthetized rats using insulated metal microelectrodes. Stimulation of the receptive field with either high intensity transcutaneous electrical pulses or with an infrared CO2 laser beam produced a biphasic increase in dorsal horn unit discharge. Conduction velocity estimates indicated that the early discharge corresponded to activity in A[delta] whereas the late response corresponded to activity in C afferent fibers. Cumulative doses of cocaine (0.1-3.1 mg/kg i.v.) inhibited the late response to either electrical or laser stimulation in a dose-related manner. The early response to laser, but not electrical, stimulation was also suppressed by cocaine. Neurons in the spinal dorsal horn with receptive fields on the ipsilateral hindpaw were activated by natural noxious (pinch) or innocuous (tap) somatic stimulation. Cocaine selectively suppressed nociceptively evoked dorsal horn unit discharge. This antinociceptive effect was dose-related (0.3-3.1 mg/kg, i.v.) and antagonized by eticlopride (0.05-0.1 mg/kg, i.v.), a selective D2 dopamine receptor blocker. The same doses of cocaine failed to inhibit the responses of dorsal horn neurons to low threshold innocuous stimulation. Complete thoracic spinal cord transection eliminated the antinociceptive effect of cocaine on dorsal horn neurons and also eliminated the cocaine-induced attenuation of the tail-flick reflex. These data demonstrte that cocaine selectively inhibits nociceptive spinal reflexes and the nociceptive responses of dorsal horn neurons primarily by means of a D2 dopaminergic receptor mechanism. This antinociceptive effect of cocaine is independent of its local anesthetic activity and requires the integrity of the thoracic spinal cord, suggesting that the drug potentiates or activates supraspinal dopaminergic projections to the dorsal horn.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31630/1/0000564.pd

Metastable liquid-liquid phase transition in a single-component system with only one crystal phase and no density anomaly

We investigate the phase behavior of a single-component system in 3 dimensions with spherically-symmetric, pairwise-additive, soft-core interactions with an attractive well at a long distance, a repulsive soft-core shoulder at an intermediate distance, and a hard-core repulsion at a short distance, similar to potentials used to describe liquid systems such as colloids, protein solutions, or liquid metals. We showed [Nature {\bf 409}, 692 (2001)] that, even with no evidences of the density anomaly, the phase diagram has two first-order fluid-fluid phase transitions, one ending in a gas--low-density liquid (LDL) critical point, and the other in a gas--high-density liquid (HDL) critical point, with a LDL-HDL phase transition at low temperatures. Here we use integral equation calculations to explore the 3-parameter space of the soft-core potential and we perform molecular dynamics simulations in the interesting region of parameters. For the equilibrium phase diagram we analyze the structure of the crystal phase and find that, within the considered range of densities, the structure is independent of the density. Then, we analyze in detail the fluid metastable phases and, by explicit thermodynamic calculation in the supercooled phase, we show the absence of the density anomaly. We suggest that this absence is related to the presence of only one stable crystal structure.Comment: 15 pages, 21 figure

Expression of nuclear retinoid receptors in normal, premalignant and malignant gastric tissues determined by in situ hybridization

[[abstract]]Retinoids exhibit multiple functions through interaction with nuclear retinoid receptors and have growth-suppressive activity on gastric cancer cells. To better understand the roles of nuclear retinoid receptors during gastric carcinogenesis, we have used in situ hybridization to investigate expression of retinoic acid receptors (RARs) and retinoid x receptors (RXRs) in premalignant and malignant formalin-fixed paraffin-embedded gastric tissues. Histological sections of eight normal, 17 distal normal and nine gastric cancer tissues were hybridized with non-radioactive RNA probes for subtypes of RAR and RXR. Expression of RARα, RARβ, RARγ, RXRα and RXRβ was found in most cell types in gastric mucosa tissues from normal individuals as well as in distal normal tissues from cancer patients. Expression of RARα and RARβ were found in three and seven cancer tissues, respectively, and levels of RXRα mRNA were significantly decreased in poorly differentiated cancer tissues. Among the five investigated nuclear retinoid receptors, only expression of RARα mRNA was significantly decreased in intestinal metaplasia, dysplasia and cancer tissues when compared to adjacent normal tissues. In conclusion, normal gastric mucosa expressed both RARs and RXRs, which supports the physiological role of retinoic acid on normal gastric mucosa. The decrease in RARα expression in premalignant and malignant gastric tissues suggests a significant role of RARα during gastric carcinogenesis.[[notice]]補正完畢[[incitationindex]]SC