Statistical analysis and modeling for biomolecular structures

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Kumar, Vibhor 2012-02-24T08:29:46Z 2012-02-24T08:29:46Z 2007-08-17
dc.identifier.isbn 978-951-22-8891-5
dc.identifier.issn 1455-0474
dc.description.abstract Most of the recent studies on biomolecules address their three dimensional structure since it is closely related to their functions in a biological system. Determination of structure of biomolecules can be done by using various methods, which rely on data from various experimental instruments or on computational approaches to previously obtained data or datasets. Single particle reconstruction using electron microscopic images of macromolecules has proven resource-wise to be useful and affordable for determining their molecular structure in increasing details. The main goal of this thesis is to contribute to the single particle reconstruction methodology, by adding a process of denoising in the analysis of the cryo-electron microscopic images. First, the denoising methods are briefly surveyed and their efficiencies for filtering cryo-electron microscopic images are evaluated. In this thesis, the focus has been set to information theoretic minimum description length (MDL) principle for coding efficiently the essential part of the signal. This approach can also be applied to reduce noise in signals and here it is used to develop a novel denoising method for cryo-electron microscopic images. An existing denoising method has been modified to suit the given problem in single particle reconstruction. In addition, a more general denoising method has been developed, discovering a novel way to find model class by using the MDL principle. This method was then thoroughly tested and compared with co-existing methods in order to evaluate the utility of denoising in single particle reconstruction. A secondary goal in the research for this thesis deals with studying protein oligomerisation, using computational approaches. The focus has been to recognize interacting residues in proteins for oligomerization and to model the interaction site for hantavirus N-protein. In order to unravel the interaction structure, the approach has been to understand the phenomenon of protein folding towards quaternary structure. en
dc.format.extent 56, [56]
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries Helsinki University of Technology Laboratory of Computational Engineering publications. Report B en
dc.relation.ispartofseries 62 en
dc.relation.haspart [Publication 1]: Vibhor Kumar, Jukka Heikkonen, Peter Engelhardt and Kimmo Kaski, Robust filtering and particle picking in micrograph images towards 3D reconstruction of purified proteins with cryo-electron microscopy, Journal of Structural Biology, 145 (1-2): 41-51, 2004.
dc.relation.haspart [Publication 2]: Pasi Kaukinen, Vibhor Kumar, Kirsi Tulimäki, Peter Engelhardt, Antti Vaheri and Alexander Plyusnin, Oligomerization of hantavirus N protein: C-terminal α-helices interact to form a shared hydrophobic space, Journal of Virology, 78 (24): 13669-13677, 2004. © 2004 American Society for Microbiology (ASM). By permission.
dc.relation.haspart [Publication 3]: Vibhor Kumar, Jukka Heikkonen, Jorma Rissanen and Kimmo Kaski, Minimum description length denoising with histogram models, IEEE Transactions on Signal Processing, 54 (8): 2922-2928, 2006. © 2006 IEEE. By permission.
dc.relation.haspart [Publication 4]: Vibhor Kumar and Jukka Heikkonen, Denoising with flexible histogram models on Minimum Description length principle, in B. Enyedi and T. Farhinger, editors, Proceedings of the 13th International Conference on Systems, Signals and Image Processing (IWSSIP 2006), pp: 167-172, Budapest, Hungary, 2006.
dc.relation.haspart [Publication 5]: Agne Alminaite, Vera Halttunen, Vibhor Kumar, Antti Vaheri, Liisa Holm and Alexander Plyusnin, Oligomerization of hantavirus nucleocapsid protein: analysis of the N-terminal coiled-coil domain, Journal of Virology, 80 (18): 9073-9081, 2006. © 2006 American Society for Microbiology (ASM). By permission.
dc.subject.other Physics en
dc.subject.other Electrical engineering en
dc.title Statistical analysis and modeling for biomolecular structures en
dc.type G5 Artikkeliväitöskirja fi
dc.description.version reviewed en
dc.contributor.department Department of Electrical and Communications Engineering en
dc.contributor.department Sähkö- ja tietoliikennetekniikan osasto fi
dc.subject.keyword MDL denoising en
dc.subject.keyword cryo-EM en
dc.subject.keyword biomolecular structure en
dc.identifier.urn urn:nbn:fi:tkk-009530
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.lab Laboratory of Computational Engineering en
dc.contributor.lab Laskennallisen tekniikan laboratorio fi

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