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Sample records for mitteosalenud naiste teadlikkus

  1. Genetic Analysis of Collective Motility of Paenibacillus sp. NAIST15-1

    PubMed Central

    Kobayashi, Kazuo; Kanesaki, Yu

    2016-01-01

    Bacteria have developed various motility mechanisms to adapt to a variety of solid surfaces. A rhizosphere isolate, Paenibacillus sp. NAIST15-1, exhibited unusual motility behavior. When spotted onto 1.5% agar media, Paenibacillus sp. formed many colonies, each of which moved around actively at a speed of 3.6 μm/sec. As their density increased, each moving colony began to spiral, finally forming a static round colony. Despite its unusual motility behavior, draft genome sequencing revealed that both the composition and organization of flagellar genes in Paenibacillus sp. were very similar to those in Bacillus subtilis. Disruption of flagellar genes and flagellar stator operons resulted in loss of motility. Paenibacillus sp. showed increased transcription of flagellar genes and hyperflagellation on hard agar media. Thus, increased flagella and their rotation drive Paenibacillus sp. motility. We also identified a large extracellular protein, CmoA, which is conserved only in several Paenibacillus and related species. A cmoA mutant could neither form moving colonies nor move on hard agar media; however, motility was restored by exogenous CmoA. CmoA was located around cells and enveloped cell clusters. Comparison of cellular behavior between the wild type and cmoA mutant indicated that extracellular CmoA is involved in drawing water out of agar media and/or smoothing the cell surface interface. This function of CmoA probably enables Paenibacillus sp. to move on hard agar media. PMID:27764113

  2. Thermoelectric Transducer Using Bio Nano Process

    DTIC Science & Technology

    2015-08-01

    Science and Technology 8916-5, Takayama, Ikoma, Nara Nara 630-0192 Japan 8. PERFORMING ORGANIZATION REPORT NUMBER N/A 9. SPONSORING...Graduate School of Material Science Nara Institute of Science and Technology 8916-5 Takayama, Ikoma, Nara 630-0192, Japan uraoka@ms.naist.jp. KEYWORDS

  3. KNApSAcK-3D: a three-dimensional structure database of plant metabolites.

    PubMed

    Nakamura, Kensuke; Shimura, Naoki; Otabe, Yuuki; Hirai-Morita, Aki; Nakamura, Yukiko; Ono, Naoaki; Ul-Amin, Md Altaf; Kanaya, Shigehiko

    2013-02-01

    Studies on plant metabolites have attracted significant attention in recent years. Over the past 8 years, we have constructed a unique metabolite database, called KNApSAcK, that contains information on the relationships between metabolites and their expressing organism(s). In the present paper, we introduce KNApSAcK-3D, which contains the three-dimensional (3D) structures of all of the metabolic compounds included in the original KNApSAcK database. The 3D structure for each compound was optimized using the Merck Molecular Force Field (MMFF94), and a multiobjective genetic algorithm was used to search extensively for possible conformations and locate the global minimum. The resulting set of structures may be used for docking studies to identify new and potentially unexpected binding sites for target proteins. The 3D structures may also be utilized for more qualitative studies, such as the estimation of biological activities using 3D-QSAR. The database can be accessed via a link from the KNApSAcK Family website (http://kanaya.naist.jp/KNApSAcK_Family/) or directory at http://kanaya.naist.jp/knapsack3d/.

  4. IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming.

    PubMed

    Sato, Kengo; Kato, Yuki; Hamada, Michiaki; Akutsu, Tatsuya; Asai, Kiyoshi

    2011-07-01

    Pseudoknots found in secondary structures of a number of functional RNAs play various roles in biological processes. Recent methods for predicting RNA secondary structures cover certain classes of pseudoknotted structures, but only a few of them achieve satisfying predictions in terms of both speed and accuracy. We propose IPknot, a novel computational method for predicting RNA secondary structures with pseudoknots based on maximizing expected accuracy of a predicted structure. IPknot decomposes a pseudoknotted structure into a set of pseudoknot-free substructures and approximates a base-pairing probability distribution that considers pseudoknots, leading to the capability of modeling a wide class of pseudoknots and running quite fast. In addition, we propose a heuristic algorithm for refining base-paring probabilities to improve the prediction accuracy of IPknot. The problem of maximizing expected accuracy is solved by using integer programming with threshold cut. We also extend IPknot so that it can predict the consensus secondary structure with pseudoknots when a multiple sequence alignment is given. IPknot is validated through extensive experiments on various datasets, showing that IPknot achieves better prediction accuracy and faster running time as compared with several competitive prediction methods. The program of IPknot is available at http://www.ncrna.org/software/ipknot/. IPknot is also available as a web server at http://rna.naist.jp/ipknot/. satoken@k.u-tokyo.ac.jp; ykato@is.naist.jp Supplementary data are available at Bioinformatics online.

  5. GenoBase: comprehensive resource database of Escherichia coli K-12

    PubMed Central

    Otsuka, Yuta; Muto, Ai; Takeuchi, Rikiya; Okada, Chihiro; Ishikawa, Motokazu; Nakamura, Koichiro; Yamamoto, Natsuko; Dose, Hitomi; Nakahigashi, Kenji; Tanishima, Shigeki; Suharnan, Sivasundaram; Nomura, Wataru; Nakayashiki, Toru; Aref, Walid G.; Bochner, Barry R.; Conway, Tyrrell; Gribskov, Michael; Kihara, Daisuke; Rudd, Kenneth E.; Tohsato, Yukako; Wanner, Barry L.; Mori, Hirotada

    2015-01-01

    Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources. PMID:25399415

  6. GenoBase: comprehensive resource database of Escherichia coli K-12.

    PubMed

    Otsuka, Yuta; Muto, Ai; Takeuchi, Rikiya; Okada, Chihiro; Ishikawa, Motokazu; Nakamura, Koichiro; Yamamoto, Natsuko; Dose, Hitomi; Nakahigashi, Kenji; Tanishima, Shigeki; Suharnan, Sivasundaram; Nomura, Wataru; Nakayashiki, Toru; Aref, Walid G; Bochner, Barry R; Conway, Tyrrell; Gribskov, Michael; Kihara, Daisuke; Rudd, Kenneth E; Tohsato, Yukako; Wanner, Barry L; Mori, Hirotada

    2015-01-01

    Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Detection of multiscale pockets on protein surfaces using mathematical morphology.

    PubMed

    Kawabata, Takeshi

    2010-04-01

    Detection of pockets on protein surfaces is an important step toward finding the binding sites of small molecules. In a previous study, we defined a pocket as a space into which a small spherical probe can enter, but a large probe cannot. The radius of the large probes corresponds to the shallowness of pockets. We showed that each type of binding molecule has a characteristic shallowness distribution. In this study, we introduced fundamental changes to our previous algorithm by using a 3D grid representation of proteins and probes, and the theory of mathematical morphology. We invented an efficient algorithm for calculating deep and shallow pockets (multiscale pockets) simultaneously, using several different sizes of spherical probes (multiscale probes). We implemented our algorithm as a new program, ghecom (grid-based HECOMi finder). The statistics of calculated pockets for the structural dataset showed that our program had a higher performance of detecting binding pockets, than four other popular pocket-finding programs proposed previously. The ghecom also calculates the shallowness of binding ligands, R(inaccess) (minimum radius of inaccessible spherical probes) that can be obtained from the multiscale molecular volume. We showed that each part of the binding molecule had a bias toward a specific range of shallowness. These findings will be useful for predicting the types of molecules that will be most likely to bind putative binding pockets, as well as the configurations of binding molecules. The program ghecom is available through the Web server (http://biunit.naist.jp/ghecom).

  8. PREFACE: Nanosafe2010: International Conference on Safe Production and Use of Nanomaterials

    NASA Astrophysics Data System (ADS)

    Sentein, Carole; Schuster, Frédéric; Tardif, François

    2011-07-01

    -Tech Innovation Ltd, GB DASKALOS MCERTH/CPERI, GR DE BERARDIS BIstituto Superiore di Sanità, IT DE MIGUEL YTECNALIA, ES DELAHAYE AAd Air Solutions, FR DEMIDOVA TSevertsov Inst. of Ecology and Evolution, RU DENOO KSolae, GR DERROUGH SCEA, FR DOBRZYNSKA E BCentral Institute for Labour Protection, PL DOLEZ PÉcole de technologie supérieure, CA DOUKI TCEA, FR DRAIS EINRS, FR DUFOUR J-PCILAS, FR DURAN NUNICAMP, BR DURAND CCEA, FR DUTOUQUET CINERIS, FR DUVAL-ARNOULD GSaint-Gobain, FR ECKHOFF R KUniv. Bergen, NO ELLENBECKER M JUniv. Massachusetts Lowell, US EMOND CUniv. Montreal, CA ENGEL SBASF, DE ESTRELA-LOPIS ILeipzig Univ., DE FABBRI MJRC, IT FACCINI MLeitat technological center, ES FESSARD VAnses, FR FILIMUNDI ETSI, DE FIRSTOVA VSRCAMB, RU FLEURY DINERIS, FR FRABOULET DCEA, FR FRESNAY CThales Research & Technology, FR GABORIEAU ACEA, FR GAFFET ENanoMaterials Research Group, FR GALLET SCefic, BE GEIGER DBASF, DE GENSDARMES FIRSN, FR GERRITSEN-EBBEN RTNO Quality of Life, NL GKANIS VDemokritos, GR GLUSHKOVA ARIHOPHE, RU GONZALEZ-FERNANDEZ AUniv. Vigo, ES GOOSSENS HPhilips Research Aerasense, NL GRAHNSTEDT SOslo Univ., NO GREENHILL-HOOPER MRio Tinto Minerals, FR GROSSEAU PEcole des Mines de Saint Etienne, FR GUADAGNINI RUniv. Paris 7 Diderot, FR GUIOT ACEA, FR GUIZARD BCEA, FR HAASE AFederal Institute for Risk Assessment, DE HANINI AUniv. Paris 7 Diderot, FR HAYNES LUniv. de los Andes, VE HEJAZI MUniv. Tehran, IR HENRY FINERIS, FR HERRERA HInstitute for Work and Health, CH HOET PKU Leuven, BE HOLE PNanosight, GB HULME JUniv. Cambridge, GB JI XINERIS, FR JOUHANNAUD JCEA, FR JOUZEL J-NCenter for the Sociology of Organizations, FR JURKSCHAT KOxford Univ., GB KAISER J-PEmpa, CH KANAYA FNat. Center for Global Health and Medicine, JP KATALAGARIANAKIS GEuropean Commission, BE KECK LGrimm Aerosol Technik, DE KELLER MFraunhofer Institute, DE KHLEBNIKOVA NRIHOPHE, RU KHODABANDEH MUniv. Tehran, IR KHOLODENKO VSRCAMB, RU KOBAYASHI NAIST, JP KOPONEN INRCWE, DK KOWAL SINERIS, FR KRYSANOV