The Experts below are selected from a list of 308100 Experts worldwide ranked by ideXlab platform
Yukio Sugiura - One of the best experts on this subject based on the ideXlab platform.
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New insights into sequence Recognition Process of esperamicin A1 and calicheamicin gamma 1I.: origin of their selectivities and "induced fit" mechanism.
Biochemistry, 1993Co-Authors: Motonari Uesugi, Yukio SugiuraAbstract:: This study addresses the DNA sequence Recognition event of the enediyne antibiotics esperamicin A1 and calicheamicin gamma 1I by the use of synthetic DNA oligomers, salt effects, and circular dichroism studies. The results reported here provide several important insights: (1) esperamicin A1 requires a purine/pyrimidine trimer in host DNA for favorable interaction, (2) the sequence selectivity of esperamicin C is an origin of esperamicin A1 and calicheamicin gamma 1I selectivities, (3) in the target Recognition by esperamicin C, its total structure and hydrophobicity are important, and (4) the binding of hydrophobic esperamicin to DNA duplex induces dehydration and conformational change of the host DNA. The specific sequence Recognition Process of esperamicin/calicheamicin has been discussed.
Laurent Heutte - One of the best experts on this subject based on the ideXlab platform.
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combination of contextual information for handwritten word Recognition
International Conference on Frontiers in Handwriting Recognition, 2004Co-Authors: Guillaume Koch, Thierry Paquet, Laurent HeutteAbstract:In this paper, we present a method for the Recognition of handwritten words extracted from real incoming mail documents. The word Recognition Process is based on three different sources of information: outputs of a character classifier, contextual information extracted from word shapes and some a priori knowledge. Reported results demonstrate the benefit of those additional information on the word Recognition rates. This approach is evaluated on a database of 5000 words= examples.
Motonari Uesugi - One of the best experts on this subject based on the ideXlab platform.
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New insights into sequence Recognition Process of esperamicin A1 and calicheamicin gamma 1I.: origin of their selectivities and "induced fit" mechanism.
Biochemistry, 1993Co-Authors: Motonari Uesugi, Yukio SugiuraAbstract:: This study addresses the DNA sequence Recognition event of the enediyne antibiotics esperamicin A1 and calicheamicin gamma 1I by the use of synthetic DNA oligomers, salt effects, and circular dichroism studies. The results reported here provide several important insights: (1) esperamicin A1 requires a purine/pyrimidine trimer in host DNA for favorable interaction, (2) the sequence selectivity of esperamicin C is an origin of esperamicin A1 and calicheamicin gamma 1I selectivities, (3) in the target Recognition by esperamicin C, its total structure and hydrophobicity are important, and (4) the binding of hydrophobic esperamicin to DNA duplex induces dehydration and conformational change of the host DNA. The specific sequence Recognition Process of esperamicin/calicheamicin has been discussed.
Marco Morana - One of the best experts on this subject based on the ideXlab platform.
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human activity Recognition Process using 3 d posture data
IEEE Transactions on Human-Machine Systems, 2015Co-Authors: Salvatore Gaglio, Giuseppe Lo Re, Marco MoranaAbstract:In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution outperforms four relevant works based on RGB-D image fusion , hierarchical Maximum Entropy Markov Model , Markov Random Fields , and Eigenjoints , respectively. The performance we achieved, i.e., precision/recall of 77.3% and 76.7%, and the ability to recognize the activities in real time show promise for applied use.
Jerzy Leszczynski - One of the best experts on this subject based on the ideXlab platform.
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molecular basis of the Recognition Process hydrogen bonding patterns in the guanine primary Recognition site of ribonuclease t1
Journal of Physical Chemistry B, 2006Co-Authors: Jing Wang, Jerzy LeszczynskiAbstract:Investigation of the intrinsic H-bonding pattern of the guanine complex with a sizable segment (from Asn43 to Glu46) of the primary Recognition site (PRS) in RNase T1 at the B3LYP/6-311G(d,p) level of theory enables the electronic density characteristics of the H-bonding patterns of the guanine−PRS complexes to be identified. The perfect H-bonding pattern in the guanine Recognition site is achieved through the guanine complex interactions with the large segment of the PRS. Two significant short H-bonds, Oe1···HN1 and Oe2···HN2, have been identified. The similar short H-bond distances found in the anionic GC- base pair and in this study suggest that the short hydrogen-bond distances may be characteristic of the multiple H-bonded anionic nucleobases. The H-bonding energy distribution, the geometric analysis of the H-bonding pattern, and the electron structure characteristics of the H-bonds in the guanine PRS of RNase T1 all suggest that the Oe1···HN1 and Oe2···HN2 side-chain H-bonds dominate the binding at ...
