Institution
Nara Institute of Science and Technology
Education•Ikoma, Japan•
About: Nara Institute of Science and Technology is a education organization based out in Ikoma, Japan. It is known for research contribution in the topics: Gene & Photoluminescence. The organization has 7197 authors who have published 14210 publications receiving 419295 citations. The organization is also known as: Nara Sentan Kagaku Gijutsu Daigakuin Daigaku.
Topics: Gene, Photoluminescence, Arabidopsis, Scintillation, Luminescence
Papers published on a yearly basis
Papers
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TL;DR: These mutants—the ‘Keio collection’—provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome‐wide testing of mutational effects in a common strain background, E. coli K‐12 BW25113.
Abstract: We have systematically made a set of precisely defined, single-gene deletions of all nonessential genes in Escherichia coli K-12. Open-reading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a one-step method for inactivation of chromosomal genes and primers designed to create in-frame deletions upon excision of the resistance cassette. Of 4288 genes targeted, mutants were obtained for 3985. To alleviate problems encountered in high-throughput studies, two independent mutants were saved for every deleted gene. These mutants-the 'Keio collection'-provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome-wide testing of mutational effects in a common strain background, E. coli K-12 BW25113. We were unable to disrupt 303 genes, including 37 of unknown function, which are candidates for essential genes. Distribution is being handled via GenoBase (http://ecoli.aist-nara.ac.jp/).
7,428 citations
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TL;DR: Bacillus subtilis is the best-characterized member of the Gram-positive bacteria, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.
Abstract: Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.
3,753 citations
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TL;DR: Nanog is a critical factor underlying pluripotency in both ICM and ES cells, and it is found that one of them, encoding the homeoprotein Nanog, was capable of maintaining ES cell self-renewal independently of LIF/Stat3.
3,321 citations
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TL;DR: T tandem affinity purification was used to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae to identify protein–protein interactions, which will help future studies on individual proteins as well as functional genomics and systems biology.
Abstract: Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.
2,975 citations
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TL;DR: Rho appears to inhibit myosin phosphatase through the action of Rho-kinase, which is activated by GTP·RhoA, phosphorylation of MBS and MLC in NIH 3T3 cells.
Abstract: The small guanosine triphosphatase Rho is implicated in myosin light chain (MLC) phosphorylation, which results in contraction of smooth muscle and interaction of actin and myosin in nonmuscle cells. The guanosine triphosphate (GTP)-bound, active form of RhoA (GTP.RhoA) specifically interacted with the myosin-binding subunit (MBS) of myosin phosphatase, which regulates the extent of phosphorylation of MLC. Rho-associated kinase (Rho-kinase), which is activated by GTP.RhoA, phosphorylated MBS and consequently inactivated myosin phosphatase. Overexpression of RhoA or activated RhoA in NIH 3T3 cells increased phosphorylation of MBS and MLC. Thus, Rho appears to inhibit myosin phosphatase through the action of Rho-kinase.
2,899 citations
Authors
Showing all 7226 results
Name | H-index | Papers | Citations |
---|---|---|---|
Kozo Kaibuchi | 129 | 493 | 60461 |
Shigekazu Nagata | 124 | 428 | 85675 |
Krzysztof Palczewski | 114 | 631 | 46909 |
Katsuhiko Ariga | 112 | 864 | 45242 |
Shinya Yamanaka | 111 | 394 | 98438 |
Shunichi Fukuzumi | 111 | 1256 | 52764 |
Seiji Shinkai | 103 | 1158 | 48059 |
Charles Boone | 100 | 294 | 42217 |
Masaya Tohyama | 96 | 726 | 36055 |
Mitsuhiro Yanagida | 94 | 306 | 31224 |
Gen Sobue | 91 | 947 | 36378 |
Yoshiharu Matsuura | 88 | 418 | 33138 |
Kensuke Egashira | 88 | 335 | 26822 |
Naoto Chatani | 87 | 597 | 26370 |
Mitsuo Kawato | 86 | 422 | 35640 |