21,692 research outputs found
Development of method of matched morphological filtering of biomedical signals and images
Formalized approach to the analysis of biomedical signals and images with locally concentrated features is developed on the basis of matched morphological filtering taking into account the useful signal models that allowed generalizing the existing methods of digital processing and analysis of biomedical signals and images with locally concentrated features. The proposed matched morphological filter has been adapted to solve such problems as localization of the searched structural elements on biomedical signals with locally concentrated features, estimation of the irregular background aimed at the visualization quality improving of biological objects on X-ray biomedical images, pathologic structures selection on mammogram. The efficiency of the proposed methods of matched morphological filtration of biomedical signals and images with locally concentrated features is proved by experiments
The Phyre2 web portal for protein modeling, prediction and analysis
Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission
Solving the tasks of subsurface resources management in GIS RAPID environment
Purpose. Solving the tasks of subsurface resources management based on the created GIS RAPID geoinformation technology.
Methods. Close spatial relationships of lineament network characteristics and earthquake epicenters were detected in 3 seismically active areas located in the mountainous regions of Central Europe. Digital elevation models (DEM) based on ASTER satellite surveys and earthquake epicenter data were used. The nature of spatial relationship of lineament network and vein ore objects was studied in the territory of Congo DR, in the Lake Kivu area using space imagery. Gold ore objects were searched and forecasted in Uzbekistan in the site of Jamansai Mountains. High- resolution imagery from QuickBird 2 satellite, geophysical field surveys, geological and geochemical data were used.
Findings. It was found that a significant number of epicenters are located in areas of high concentration of ânon-standardâ azimuths lineaments â from 27 to 34% of the total number of lineaments. It was revealed that 59.6% of the epicenters are located within 10% of sites with the highest values of complex deformation maps; 50% of the areas with the highest values of these maps contain, on average, 89% of all earthquake epicenters. It was found that satellite image lineament concentration maps with ânon-standardâ azimuths reflect the spatial relationship with known deposits much better than the concentration map of all lineaments. It was detected that the total area of gold ore objects perspective sites is about 20 km2.
Originality. The use of GIS RAPID in a number of earthâs crust areas has allowed to establish new regularities linking the networks of physical field and landscape lineament characteristics with ore bodies and earthquake epicenters localization.
Practical implications. A new technology has been developed for solving geological forecasting and prospecting problems. The technology can be used to solve a wide range of practical problems, especially in difficult geological conditions when searching for deep objects weakly presented in external fields and landscape.ĐĐ”ŃĐ°. Đ ŃŃĐ”ĐœĐœŃ Đ·Đ°ĐŽĐ°Ń ĐœĐ°ĐŽŃĐŸĐșĐŸŃĐžŃŃŃĐČĐ°ĐœĐœŃ ĐœĐ° Đ±Đ°Đ·Ń ŃŃĐČĐŸŃĐ”ĐœĐŸŃÌ ĐłĐ”ĐŸŃĐœŃĐŸŃĐŒĐ°ŃŃĐžÌĐœĐŸŃÌ ŃĐ”Ń
ĐœĐŸĐ»ĐŸĐłŃŃÌ ĐĐĐĄ Đ ĐĐĐĐ.
ĐĐ”ŃĐŸĐŽĐžĐșĐ°. ĐĐžŃĐČĐ»Đ”ĐœĐœŃ ŃŃŃĐœĐžŃ
ĐżŃĐŸŃŃĐŸŃĐŸĐČĐžŃ
ĐČĐ·Đ°ŃĐŒĐŸĐ·ĐČâŃĐ·ĐșŃĐČ ŃŃĐ·ĐœĐŸĐŒĐ°ĐœŃŃĐœĐžŃ
Ń
Đ°ŃĐ°ĐșŃĐ”ŃĐžŃŃĐžĐș ĐŒĐ”ŃДж Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ Ń Đ”ĐżŃŃĐ”ĐœŃŃŃĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃŃĐČ ĐżŃĐŸĐČĐŸĐŽĐžĐ»ĐŸŃŃ Ń 3 ŃДОÌŃĐŒĐŸĐ°ĐșŃĐžĐČĐœĐžŃ
ĐŽŃĐ»ŃĐœĐșĐ°Ń
, ŃĐŸĐ·ŃĐ°ŃĐŸĐČĐ°ĐœĐžŃ
ĐČ ĐłŃŃŃŃĐșĐžŃ
ŃĐ°ĐžÌĐŸĐœĐ°Ń
ĐŠĐ”ĐœŃŃĐ°Đ»ŃĐœĐŸŃÌ ĐĐČŃĐŸĐżĐž. ĐĐžĐșĐŸŃĐžŃŃĐŸĐČŃĐČалОŃŃ ŃĐžŃŃĐŸĐČŃ ĐŒĐŸĐŽĐ”Đ»Ń ŃДлŃŃŃŃ (DEM), ĐżĐŸĐ±ŃĐŽĐŸĐČĐ°ĐœŃ Đ·Đ° Đ·ĐžÌĐŸĐŒĐșĐ°ĐŒĐž Đ·Ń ŃŃĐżŃŃĐœĐžĐșĐ° ASTER Ń ĐŽĐ°ĐœŃ ĐżĐŸ ДпŃŃĐ”ĐœŃŃĐ°Ń
Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃŃĐČ. ĐĐŸŃĐ»ŃĐŽĐ¶Đ”ĐœĐœŃ Ń
Đ°ŃĐ°ĐșŃĐ”ŃŃ ĐżŃĐŸŃŃĐŸŃĐŸĐČĐŸĐłĐŸ ĐČĐ·Đ°ŃĐŒĐŸĐ·ĐČâŃĐ·ĐșŃ ĐŒĐ”ŃĐ”Đ¶Ń Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ Ń Đ¶ĐžĐ»ŃĐœĐžŃ
ŃŃĐŽĐœĐžŃ
ĐŸĐ±âŃĐșŃŃĐČ ĐżŃĐŸĐČĐŸĐŽĐžĐ»ĐžŃŃ ĐœĐ° ŃĐ”ŃĐžŃĐŸŃŃŃÌ ĐĐ”ĐŒĐŸĐșŃĐ°ŃĐžŃĐœĐŸŃÌ Đ Đ”ŃĐżŃблŃĐșĐž ĐĐŸĐœĐłĐŸ, ĐČ ŃĐ°ĐžÌĐŸĐœŃ ĐŸĐ·Đ”ŃĐ° ĐŃĐČŃ ŃĐ· ĐČĐžĐșĐŸŃĐžŃŃĐ°ĐœĐœŃĐŒ ĐșĐŸŃĐŒŃŃĐœĐžŃ
Đ·ĐžÌĐŸĐŒĐŸĐș. ĐĐŸŃĐ»ŃĐŽĐ¶Đ”ĐœĐœŃ ĐżĐŸŃŃĐșŃ ŃĐ° ĐżŃĐŸĐłĐœĐŸĐ·Ń Đ·ĐŸĐ»ĐŸŃĐŸŃŃĐŽĐœĐžŃ
ĐŸĐ±âŃĐșŃŃĐČ ĐČĐžĐșĐŸĐœŃĐČалОŃŃ ĐČ ĐŁĐ·Đ±Đ”ĐșĐžŃŃĐ°ĐœŃ ĐœĐ° ĐŽŃĐ»ŃĐœŃŃ ĐĐ¶Đ°ĐŒĐ°ĐœŃĐ°ĐžÌŃĐșŃŃ
ĐłŃŃ. ĐĐžĐșĐŸŃĐžŃŃĐŸĐČŃĐČалОŃŃ ĐČĐžŃĐŸĐșĐŸŃĐŸŃĐœŃ ĐșĐŸŃĐŒŃŃĐœŃ Đ·ĐžÌĐŸĐŒĐșĐž Đ·Ń ŃŃĐżŃŃĐœĐžĐșĐ° QuickBird 2, Đ·ĐžÌĐŸĐŒĐșĐž ĐłĐ”ĐŸŃŃĐ·ĐžŃĐœĐžŃ
ĐżĐŸĐ»ŃĐČ, ĐłĐ”ĐŸĐ»ĐŸĐłŃŃĐœŃ ŃĐ° ĐłĐ”ĐŸŃ
ŃĐŒŃŃĐœŃ ĐŽĐ°ĐœŃ.
РДзŃĐ»ŃŃĐ°ŃĐž. ĐĐžŃĐČĐ»Đ”ĐœĐŸ, ŃĐŸ Đ·ĐœĐ°ŃĐœĐ° ŃĐ°ŃŃĐžĐœĐ° ДпŃŃĐ”ĐœŃŃŃĐČ ĐżŃĐžŃŃĐŸŃĐ”ĐœĐ° ŃĐ°ĐŒĐ” ĐŽĐŸ ĐŽŃĐ»ŃĐœĐŸĐș ĐżŃĐŽĐČĐžŃĐ”ĐœĐŸŃÌ ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃŃŃÌ Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ âĐœĐ”ŃŃĐ°ĐœĐŽĐ°ŃŃĐœĐžŃ
â Đ°Đ·ĐžĐŒŃŃŃĐČ, ŃĐșлаЎаŃŃĐž ĐČŃĐŽ 27 ĐŽĐŸ 34% загалŃĐœĐŸĐłĐŸ ŃĐžŃла Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ. ĐŃŃĐ°ĐœĐŸĐČĐ»Đ”ĐœĐŸ, ŃĐŸ 59.6% ДпŃŃĐ”ĐœŃŃŃĐČ Đ·ĐœĐ°Ń
ĐŸĐŽŃŃŃŃŃ ĐČŃĐ”ŃĐ”ĐŽĐžĐœŃ 10% ŃĐ”ŃĐžŃĐŸŃŃŃÌ ĐŽŃĐ»ŃĐœĐŸĐș, ŃĐŸ ĐČĐŸĐ»ĐŸĐŽŃŃŃŃ ĐœĐ°ĐžÌĐČĐžŃĐžĐŒĐž Đ·ĐœĐ°ŃĐ”ĐœĐœŃĐŒĐž ĐșĐŸĐŒĐżĐ»Đ”ĐșŃĐœĐžŃ
ĐșĐ°ŃŃ ĐŽĐ”ŃĐŸŃĐŒĐ°ŃŃĐžÌ; 50% ŃĐ”ŃĐžŃĐŸŃŃŃÌ Đ· ĐœĐ°ĐžÌĐČĐžŃĐžĐŒĐž Đ·ĐœĐ°ŃĐ”ĐœĐœŃĐŒĐž ŃĐžŃ
ĐșĐ°ŃŃ ĐČĐŒŃŃĐ°ŃŃŃ, ĐČ ŃĐ”ŃĐ”ĐŽĐœŃĐŸĐŒŃ, 89% ŃŃŃŃ
ДпŃŃĐ”ĐœŃŃŃĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃŃĐČ. ĐĐžĐ·ĐœĐ°ŃĐ”ĐœĐŸ, ŃĐŸ ĐșĐ°ŃŃĐž ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃŃŃÌ Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ ĐșĐŸŃĐŒĐŸĐ·ĐœŃĐŒĐșŃĐČ Đ· âĐœĐ”ŃŃĐ°ĐœĐ°ŃŃĐœĐžĐŒĐžâ Đ°Đ·ĐžĐŒŃŃĐ°ĐŒĐž Đ·ĐœĐ°ŃĐœĐŸ ĐșŃĐ°ŃĐ” ĐČŃĐŽĐŸĐ±ŃажаŃŃŃ ĐżŃĐŸŃŃĐŸŃĐŸĐČĐžĐžÌ ĐČĐ·Đ°ŃĐŒĐŸĐ·ĐČâŃĐ·ĐŸĐș Đ· ĐČŃĐŽĐŸĐŒĐžĐŒĐž ŃĐŸĐŽĐŸĐČĐžŃĐ°ĐŒĐž Ń ĐżĐŸŃŃĐČĐœŃĐœĐœŃ Đ· ĐșĐ°ŃŃĐŸŃ ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃŃŃÌ ĐČŃŃŃ
Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ. ĐŃŃĐ°ĐœĐŸĐČĐ»Đ”ĐœĐŸ, ŃĐŸ ŃŃĐŒĐ°ŃĐœĐ° ĐżĐ»ĐŸŃĐ° пДŃŃпДĐșŃĐžĐČĐœĐžŃ
ĐŽŃĐ»ŃĐœĐŸĐș Đ·ĐŸĐ»ĐŸŃĐŸŃŃĐŽĐœĐžŃ
ĐŸĐ±âŃĐșŃŃĐČ ŃĐșлала блОзŃĐșĐŸ 20 ĐșĐŒ2.
ĐĐ°ŃĐșĐŸĐČĐ° ĐœĐŸĐČĐžĐ·ĐœĐ°. ĐĐ°ŃŃĐŸŃŃĐČĐ°ĐœĐœŃ ĐĐĐĄ Đ ĐĐĐĐ ĐœĐ° ŃŃĐŽŃ ĐŽŃĐ»ŃĐœĐŸĐș Đ·Đ”ĐŒĐœĐŸŃÌ ĐșĐŸŃĐž ĐŽĐŸĐ·ĐČĐŸĐ»ĐžĐ»ĐŸ ĐČŃŃĐ°ĐœĐŸĐČĐžŃĐž ĐœĐŸĐČŃ Đ·Đ°ĐșĐŸĐœĐŸĐŒŃŃĐœĐŸŃŃŃ, ŃĐŸ Đ·ĐČâŃĐ·ŃŃŃŃ Ń
Đ°ŃĐ°ĐșŃĐ”ŃĐžŃŃĐžĐșĐž ĐŒĐ”ŃĐ”Đ¶Ń Đ»ŃĐœĐ”Đ°ĐŒĐ”ĐœŃŃĐČ ŃŃĐ·ĐžŃĐœĐžŃ
ĐżĐŸĐ»ŃĐČ Ń Đ»Đ°ĐœĐŽŃĐ°ŃŃŃ Đ· Đ»ĐŸĐșĐ°Đ»ŃĐ·Đ°ŃŃŃŃ ŃŃĐŽĐœĐžŃ
ŃŃĐ» ŃĐ° ДпŃŃĐ”ĐœŃŃŃĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃŃĐČ.
ĐŃĐ°ĐșŃĐžŃĐœĐ° Đ·ĐœĐ°ŃĐžĐŒŃŃŃŃ. Đ ĐŸĐ·ŃĐŸĐ±Đ»Đ”ĐœĐŸ ĐœĐŸĐČŃ ŃĐ”Ń
ĐœĐŸĐ»ĐŸĐłŃŃ ŃŃŃĐ”ĐœĐœŃ ĐżŃĐŸĐłĐœĐŸĐ·ĐœĐžŃ
Ń ĐżĐŸŃŃĐșĐŸĐČĐžŃ
ĐłĐ”ĐŸĐ»ĐŸĐłŃŃĐœĐžŃ
Đ·Đ°ĐČĐŽĐ°ĐœŃ, ŃĐșĐ° ĐŒĐŸĐ¶Đ” Đ·Đ°ŃŃĐŸŃĐŸĐČŃĐČĐ°ŃĐžŃŃ ĐŽĐ»Ń ĐČĐžŃŃŃĐ”ĐœĐœŃ ŃĐžŃĐŸĐșĐŸĐłĐŸ ĐșĐŸĐ»Đ° ĐżŃĐ°ĐșŃĐžŃĐœĐžŃ
Đ·Đ°ĐŽĐ°Ń, ĐŸŃĐŸĐ±Đ»ĐžĐČĐŸ Ń ŃĐșĐ»Đ°ĐŽĐœĐžŃ
ĐłĐ”ĐŸĐ»ĐŸĐłŃŃĐœĐžŃ
ŃĐŒĐŸĐČĐ°Ń
ĐżŃĐž ĐżĐŸŃŃĐșĐ°Ń
ĐłĐ»ĐžĐ±ĐŸĐșĐŸĐ·Đ°Đ»ŃгаŃŃĐžŃ
ĐŸĐ±âŃĐșŃŃĐČ, ŃĐŸ ŃĐ»Đ°Đ±ĐŸ ĐČĐžŃĐČĐ»ŃŃŃŃŃŃ ĐČ Đ·ĐŸĐČĐœŃŃĐœŃŃ
ĐżĐŸĐ»ŃŃ
Ń Đ»Đ°ĐœĐŽŃĐ°ŃŃŃ.ЊДлŃ. Đ Đ”ŃĐ”ĐœĐžŃ Đ·Đ°ĐŽĐ°Ń ĐœĐ”ĐŽŃĐŸĐżĐŸĐ»ŃĐ·ĐŸĐČĐ°ĐœĐžŃ ĐœĐ° базД ŃĐŸĐ·ĐŽĐ°ĐœĐœĐŸĐžÌ ĐłĐ”ĐŸĐžĐœŃĐŸŃĐŒĐ°ŃĐžĐŸĐœĐœĐŸĐžÌ ŃĐ”Ń
ĐœĐŸĐ»ĐŸĐłĐžĐž ĐĐĐĄ Đ ĐĐĐĐ.
ĐĐ”ŃĐŸĐŽĐžĐșĐ°. ĐŃŃĐČĐ»Đ”ĐœĐžĐ” ŃĐ”ŃĐœŃŃ
ĐżŃĐŸŃŃŃĐ°ĐœŃŃĐČĐ”ĐœĐœŃŃ
ĐČĐ·Đ°ĐžĐŒĐŸŃĐČŃĐ·Đ”ĐžÌ ŃĐ°Đ·ĐœĐŸĐŸĐ±ŃĐ°Đ·ĐœŃŃ
Ń
Đ°ŃĐ°ĐșŃĐ”ŃĐžŃŃĐžĐș ŃĐ”ŃĐ”ĐžÌ Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ Đž ŃпОŃĐ”ĐœŃŃĐŸĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃĐ”ĐœĐžĐžÌ ĐżŃĐŸĐČĐŸĐŽĐžĐ»ĐŸŃŃ ĐČ 3 ŃДОÌŃĐŒĐŸĐ°ĐșŃĐžĐČĐœŃŃ
ŃŃĐ°ŃŃĐșĐ°Ń
, ŃĐ°ŃĐżĐŸĐ»ĐŸĐ¶Đ”ĐœĐœŃŃ
ĐČ ĐłĐŸŃĐœŃŃ
ŃĐ°ĐžÌĐŸĐœĐ°Ń
ĐŠĐ”ĐœŃŃĐ°Đ»ŃĐœĐŸĐžÌ ĐĐČŃĐŸĐżŃ. ĐŃĐżĐŸĐ»ŃĐ·ĐŸĐČалОŃŃ ŃĐžŃŃĐŸĐČŃĐ” ĐŒĐŸĐŽĐ”Đ»Đž ŃДлŃĐ”ŃĐ° (DEM), ĐżĐŸŃŃŃĐŸĐ”ĐœĐœŃĐ” ĐżĐŸ ŃŃĐ”ĐŒĐșĐ°ĐŒ ŃĐŸ ŃĐżŃŃĐœĐžĐșĐ° ASTER, Đž ĐŽĐ°ĐœĐœŃĐ” ĐŸĐ± ŃпОŃĐ”ĐœŃŃĐ°Ń
Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃĐ”ĐœĐžĐžÌ. ĐŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃ Ń
Đ°ŃĐ°ĐșŃĐ”ŃĐ° ĐżŃĐŸŃŃŃĐ°ĐœŃŃĐČĐ”ĐœĐœĐŸĐžÌ ĐČĐ·Đ°ĐžĐŒĐŸŃĐČŃĐ·Đž ŃĐ”ŃĐž Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ Đž жОлŃĐœŃŃ
ŃŃĐŽĐœŃŃ
ĐŸĐ±ŃĐ”ĐșŃĐŸĐČ ĐżŃĐŸĐČĐŸĐŽĐžĐ»ĐžŃŃ ĐœĐ° ŃĐ”ŃŃĐžŃĐŸŃОО ĐĐ”ĐŒĐŸĐșŃĐ°ŃĐžŃĐ”ŃĐșĐŸĐžÌ Đ Đ”ŃĐżŃблОĐșĐž ĐĐŸĐœĐłĐŸ, ĐČ ŃĐ°ĐžÌĐŸĐœĐ” ĐŸĐ·Đ”ŃĐ° ĐĐžĐČŃ Ń ĐžŃĐżĐŸĐ»ŃĐ·ĐŸĐČĐ°ĐœĐžĐ”ĐŒ ĐșĐŸŃĐŒĐžŃĐ”ŃĐșĐžŃ
ŃŃĐ”ĐŒĐŸĐș. ĐŃŃĐ»Đ”ĐŽĐŸĐČĐ°ĐœĐžŃ ĐżĐŸĐžŃĐșĐ° Đž ĐżŃĐŸĐłĐœĐŸĐ·Đ° Đ·ĐŸĐ»ĐŸŃĐŸŃŃĐŽĐœŃŃ
ĐŸĐ±ŃĐ”ĐșŃĐŸĐČ ĐČŃĐżĐŸĐ»ĐœŃлОŃŃ ĐČ ĐŁĐ·Đ±Đ”ĐșĐžŃŃĐ°ĐœĐ” ĐœĐ° ŃŃĐ°ŃŃĐșĐ” ĐĐ¶Đ°ĐŒĐ°ĐœŃĐ°ĐžÌŃĐșĐžŃ
ĐłĐŸŃ. ĐŃĐżĐŸĐ»ŃĐ·ĐŸĐČалОŃŃ ĐČŃŃĐŸĐșĐŸŃĐŸŃĐœŃĐ” ĐșĐŸŃĐŒĐžŃĐ”ŃĐșОД ŃŃĐ”ĐŒĐșĐž ŃĐŸ ŃĐżŃŃĐœĐžĐșĐ° QuickBird 2, ŃŃĐ”ĐŒĐșĐž ĐłĐ”ĐŸŃОзОŃĐ”ŃĐșĐžŃ
ĐżĐŸĐ»Đ”ĐžÌ, ĐłĐ”ĐŸĐ»ĐŸĐłĐžŃĐ”ŃĐșОД Đž ĐłĐ”ĐŸŃ
ĐžĐŒĐžŃĐ”ŃĐșОД ĐŽĐ°ĐœĐœŃĐ”.
РДзŃĐ»ŃŃĐ°ŃŃ. ĐŃŃĐČĐ»Đ”ĐœĐŸ, ŃŃĐŸ Đ·ĐœĐ°ŃĐžŃДлŃĐœĐ°Ń ŃĐ°ŃŃŃ ŃпОŃĐ”ĐœŃŃĐŸĐČ ĐżŃĐžŃŃĐŸŃĐ”ĐœĐ° ĐžĐŒĐ”ĐœĐœĐŸ Đș ŃŃĐ°ŃŃĐșĐ°ĐŒ ĐżĐŸĐČŃŃĐ”ĐœĐœĐŸĐžÌ ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃОО Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ âĐœĐ”ŃŃĐ°ĐœĐŽĐ°ŃŃĐœŃŃ
â Đ°Đ·ĐžĐŒŃŃĐŸĐČ, ŃĐŸŃŃĐ°ĐČĐ»ŃŃ ĐŸŃ 27 ĐŽĐŸ 34% ĐŸĐ±ŃĐ”ĐłĐŸ ŃĐžŃла Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ. ĐŁŃŃĐ°ĐœĐŸĐČĐ»Đ”ĐœĐŸ, ŃŃĐŸ 59.6% ŃпОŃĐ”ĐœŃŃĐŸĐČ ĐœĐ°Ń
ĐŸĐŽŃŃŃŃ ĐČĐœŃŃŃĐž 10% ŃĐ”ŃŃĐžŃĐŸŃОО ŃŃĐ°ŃŃĐșĐŸĐČ, ĐŸĐ±Đ»Đ°ĐŽĐ°ŃŃĐžŃ
ĐœĐ°ĐžĐČŃŃŃĐžĐŒĐž Đ·ĐœĐ°ŃĐ”ĐœĐžŃĐŒĐž ĐșĐŸĐŒĐżĐ»Đ”ĐșŃĐœŃŃ
ĐșĐ°ŃŃ ĐŽĐ”ŃĐŸŃĐŒĐ°ŃООÌ; 50% ŃĐ”ŃŃĐžŃĐŸŃОО Ń ĐœĐ°ĐžĐČŃŃŃĐžĐŒĐž Đ·ĐœĐ°ŃĐ”ĐœĐžŃĐŒĐž ŃŃĐžŃ
ĐșĐ°ŃŃ ĐČĐŒĐ”ŃĐ°ŃŃ, ĐČ ŃŃĐ”ĐŽĐœĐ”ĐŒ, 89% ĐČŃĐ”Ń
ŃпОŃĐ”ĐœŃŃĐŸĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃĐ”ĐœĐžĐžÌ. ĐĐżŃĐ”ĐŽĐ”Đ»Đ”ĐœĐŸ, ŃŃĐŸ ĐșĐ°ŃŃŃ ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃОО Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ ĐșĐŸŃĐŒĐŸŃĐœĐžĐŒĐșĐŸĐČ Ń âĐœĐ”ŃŃĐ°ĐœĐ°ŃŃĐœŃĐŒĐžâ Đ°Đ·ĐžĐŒŃŃĐ°ĐŒĐž Đ·ĐœĐ°ŃĐžŃДлŃĐœĐŸ Đ»ŃŃŃĐ” ĐŸŃŃажаŃŃ ĐżŃĐŸŃŃŃĐ°ĐœŃŃĐČĐ”ĐœĐœŃŃ ĐČĐ·Đ°ĐžĐŒĐŸŃĐČŃĐ·Ń Ń ĐžĐ·ĐČĐ”ŃŃĐœŃĐŒĐž ĐŒĐ”ŃŃĐŸŃĐŸĐ¶ĐŽĐ”ĐœĐžŃĐŒĐž ĐżĐŸ ŃŃĐ°ĐČĐœĐ”ĐœĐžŃ Ń ĐșĐ°ŃŃĐŸĐžÌ ĐșĐŸĐœŃĐ”ĐœŃŃĐ°ŃОО ĐČŃĐ”Ń
Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ. ĐŁŃŃĐ°ĐœĐŸĐČĐ»Đ”ĐœĐŸ, ŃŃĐŸ ŃŃĐŒĐŒĐ°ŃĐœĐ°Ń ĐżĐ»ĐŸŃĐ°ĐŽŃ ĐżĐ”ŃŃпДĐșŃĐžĐČĐœŃŃ
ŃŃĐ°ŃŃĐșĐŸĐČ Đ·ĐŸĐ»ĐŸŃĐŸŃŃĐŽĐœŃŃ
ĐŸĐ±ŃĐ”ĐșŃĐŸĐČ ŃĐŸŃŃĐ°ĐČОла ĐŸĐșĐŸĐ»ĐŸ 20 ĐșĐŒ2.
ĐĐ°ŃŃĐœĐ°Ń ĐœĐŸĐČĐžĐ·ĐœĐ°. ĐŃĐžĐŒĐ”ĐœĐ”ĐœĐžĐ” ĐĐĐĄ Đ ĐĐĐĐ ĐœĐ° ŃŃĐŽĐ” ŃŃĐ°ŃŃĐșĐŸĐČ Đ·Đ”ĐŒĐœĐŸĐžÌ ĐșĐŸŃŃ ĐżĐŸĐ·ĐČĐŸĐ»ĐžĐ»ĐŸ ŃŃŃĐ°ĐœĐŸĐČĐžŃŃ ĐœĐŸĐČŃĐ” Đ·Đ°ĐșĐŸĐœĐŸĐŒĐ”ŃĐœĐŸŃŃĐž, ŃĐČŃĐ·ŃĐČĐ°ŃŃОД Ń
Đ°ŃĐ°ĐșŃĐ”ŃĐžŃŃĐžĐșĐž ŃĐ”ŃĐž Đ»ĐžĐœĐ”Đ°ĐŒĐ”ĐœŃĐŸĐČ ŃОзОŃĐ”ŃĐșĐžŃ
ĐżĐŸĐ»Đ”ĐžÌ Đž Đ»Đ°ĐœĐŽŃĐ°ŃŃĐ° Ń Đ»ĐŸĐșалОзаŃĐžĐ”ĐžÌ ŃŃĐŽĐœŃŃ
ŃДл Đž ŃпОŃĐ”ĐœŃŃĐŸĐČ Đ·Đ”ĐŒĐ»Đ”ŃŃŃŃĐ”ĐœĐžĐžÌ.
ĐŃĐ°ĐșŃĐžŃĐ”ŃĐșĐ°Ń Đ·ĐœĐ°ŃĐžĐŒĐŸŃŃŃ. Đ Đ°Đ·ŃĐ°Đ±ĐŸŃĐ°ĐœĐ° ĐœĐŸĐČĐ°Ń ŃĐ”Ń
ĐœĐŸĐ»ĐŸĐłĐžŃ ŃĐ”ŃĐ”ĐœĐžŃ ĐżŃĐŸĐłĐœĐŸĐ·ĐœŃŃ
Đž ĐżĐŸĐžŃĐșĐŸĐČŃŃ
ĐłĐ”ĐŸĐ»ĐŸĐłĐžŃĐ”ŃĐșĐžŃ
Đ·Đ°ĐŽĐ°Ń, ĐșĐŸŃĐŸŃĐ°Ń ĐŒĐŸĐ¶Đ”Ń ĐżŃĐžĐŒĐ”ĐœŃŃŃŃŃ ĐŽĐ»Ń ŃĐ”ŃĐ”ĐœĐžŃ ŃĐžŃĐŸĐșĐŸĐłĐŸ ĐșŃŃга ĐżŃĐ°ĐșŃĐžŃĐ”ŃĐșĐžŃ
Đ·Đ°ĐŽĐ°Ń, ĐŸŃĐŸĐ±Đ”ĐœĐœĐŸ ĐČ ŃĐ»ĐŸĐ¶ĐœŃŃ
ĐłĐ”ĐŸĐ»ĐŸĐłĐžŃĐ”ŃĐșĐžŃ
ŃŃĐ»ĐŸĐČĐžŃŃ
ĐżŃĐž ĐżĐŸĐžŃĐșĐ°Ń
глŃĐ±ĐŸĐșĐŸĐ·Đ°Đ»Đ”ĐłĐ°ŃŃĐžŃ
ĐŸĐ±ŃĐ”ĐșŃĐŸĐČ, ŃĐ»Đ°Đ±ĐŸ ĐżŃĐŸŃĐČĐ»ŃŃŃĐžŃ
ŃŃ ĐČĐŸ ĐČĐœĐ”ŃĐœĐžŃ
ĐżĐŸĐ»ŃŃ
Đž Đ»Đ°ĐœĐŽŃĐ°ŃŃĐ”.The work is performed as a part of planned research of the geoinformation systems department of the Dnipro University of Technology. The results are obtained without any financial support of grants and research projects. The authors express appreciation to reviewers and editors for their valuable comments, recommendations, and attention to the work
Multimedia information technology and the annotation of video
The state of the art in multimedia information technology has not progressed to the point where a single solution is available to meet all reasonable needs of documentalists and users of video archives. In general, we do not have an optimistic view of the usability of new technology in this domain, but digitization and digital power can be expected to cause a small revolution in the area of video archiving. The volume of data leads to two views of the future: on the pessimistic side, overload of data will cause lack of annotation capacity, and on the optimistic side, there will be enough data from which to learn selected concepts that can be deployed to support automatic annotation. At the threshold of this interesting era, we make an attempt to describe the state of the art in technology. We sample the progress in text, sound, and image processing, as well as in machine learning
Structural alphabets derived from attractors in conformational space
Background: The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis.Results: A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness.Conclusions: The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics. © 2010 Pandini et al; licensee BioMed Central Ltd
How to perform RT-qPCR accurately in plant species?: a case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population
Background: Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population.
Results: An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H.
Conclusions: Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway
Advancing transcriptome platforms
During the last decade of years, remarkable technological innovations have emerged that allow the direct or indirect determination of the transcriptome at unprecedented scale and speed. Studies using these methods have already altered our view of the extent and complexity of transcript profiling, which has advanced from one-gene-at-a-time to a holistic view of the genome. Here, we outline the major technical advances in transcriptome characterization, including the most popular used hybridization-based platform, the well accepted tag-based sequencing platform, and the recently developed RNA-Seq (RNA sequencing) based platform. Importantly, these next-generation technologies revolutionize assessing the entire transcriptome via the recent RNA-Seq technology
Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications.
Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression
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