852 resultados para Image Processing in Molecular Biology Research


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,The molecular dynamics research of the core domain of p53 protein crystal structure shows that besides the stability in biochemistry this domain also shows a high stability in molecular mechanics. Based on that work, the residue R249 was substituted with amino acids Gly and Ser respectively, and molecular dynamics researches were performed separately. The results show that these substitutions cause a relax tendency between loop2 and 3 domains, leading to an alteration of the whole conformation of p53 core domain and ruining its stability. The results visually explains the mechanism of p53 changes in immunological and biochemical reactions, which are caused by 249 residue substitutions from 3-D structure variations.

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Non-invasive real time in vivo molecular imaging in small animal models has become the essential bridge between in vitro data and their translation into clinical applications. The tremendous development and technological progress, such as tumour modelling, monitoring of tumour growth and detection of metastasis, has facilitated translational drug development. This has added to our knowledge on carcinogenesis. The modalities that are commonly used include Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), bioluminescence imaging, fluorescence imaging and multi-modality imaging systems. The ability to obtain multiple images longitudinally provides reliable information whilst reducing animal numbers. As yet there is no one modality that is ideal for all experimental studies. This review outlines the instrumentation available together with corresponding applications reported in the literature with particular emphasis on cancer research. Advantages and limitations to current imaging technology are discussed and the issues concerning small animal care during imaging are highlighted.

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Current understanding of risk associated with low-dose radiation exposure has for many years been embedded in the linear-no-threshold (LNT) approach, based on simple extrapolation from the Japanese atomic bomb survivors. Radiation biology research has supported the LNT approach although much of this has been limited to relatively high-dose studies. Recently, with new advances for studying effects of low-dose exposure in experimental models and advances in molecular and cellular biology, a range of new effects of biological responses to radiation has been observed. These include genomic instability, adaptive responses and bystander effects. Most have one feature in common in that they are observed at low doses and suggest significant non-linear responses. These new observations pose a significant challenge to our understanding of low-dose exposure and require further study to elucidate mechanisms and determine their relevance.

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Background: Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism.

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Current data-intensive image processing applications push traditional embedded architectures to their limits. FPGA based hardware acceleration is a potential solution but the programmability gap and time consuming HDL design flow is significant. The proposed research approach to develop “FPGA based programmable hardware acceleration platform” that uses, large number of Streaming Image processing Processors (SIPPro) potentially addresses these issues. SIPPro is pipelined in-order soft-core processor architecture with specific optimisations for image processing applications. Each SIPPro core uses 1 DSP48, 2 Block RAMs and 370 slice-registers, making the processor as compact as possible whilst maintaining flexibility and programmability. It is area efficient, scalable and high performance softcore architecture capable of delivering 530 MIPS per core using Xilinx Zynq SoC (ZC7Z020-3). To evaluate the feasibility of the proposed architecture, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the color and morphology operations accelerated using multiple SIPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 and 33 times for color filtering and morphology operations respectively, with a significant reduced design effort and time.

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Portugal has been the world leader in the cork sector in terms of exports, employing ten thousands of workers. In this working activity, the permanent contact with cork may lead to the exposure to fungi, raising concerns as potential occupational hazards in cork industry. The application of molecular tools is crucial in this setting, since fungal species with faster growth rates may hide other species with clinical relevance, such as species belonging to P. glabrum and A. fumigatus complexes. A study was developed aiming at assessing fungal contamination due to Aspergillus fumigatus complex and Penicillium glabrum complex by molecular methods in three cork industries in the outskirt of Lisbon city.

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This thesis is an outcome of the investigations carried out on the development of an Artificial Neural Network (ANN) model to implement 2-D DFT at high speed. A new definition of 2-D DFT relation is presented. This new definition enables DFT computation organized in stages involving only real addition except at the final stage of computation. The number of stages is always fixed at 4. Two different strategies are proposed. 1) A visual representation of 2-D DFT coefficients. 2) A neural network approach. The visual representation scheme can be used to compute, analyze and manipulate 2D signals such as images in the frequency domain in terms of symbols derived from 2x2 DFT. This, in turn, can be represented in terms of real data. This approach can help analyze signals in the frequency domain even without computing the DFT coefficients. A hierarchical neural network model is developed to implement 2-D DFT. Presently, this model is capable of implementing 2-D DFT for a particular order N such that ((N))4 = 2. The model can be developed into one that can implement the 2-D DFT for any order N upto a set maximum limited by the hardware constraints. The reported method shows a potential in implementing the 2-D DF T in hardware as a VLSI / ASIC

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Three promising variants of autofluorescent proteins have been analyzed photophysically for their proposed use in single-molecule microscopy studies in living cells to compare their superiority to other fluorescent proteins previously reported regarding the number of photons emitted. The first variant under investigation the F46L mutant of eYFP has a 10% greater photon emission rate and > 50% slower photobleaching rate on average than the standard eYFP fluorophore. The monomeric red fluorescent protein (mRFP) has a fivefold lower photon emission rate, likely due to the monomeric content, and also a tenfold faster photobleaching rate than the DsRed fluorescent protein. In contrast, the previously reported eqfp611 has a 50% lower emission rate yet photobleaches more than a factor 2 slowly. We conclude that the F46L YFP and the eqfp611 are superior new options for single molecule imaging and tracking studies in living cells. Studies were also performed on the effects of forced quenching of multiple fluorescent proteins in sub-micrometer regions that would show the effects of dimerization at low concentration levels of fluorescent proteins and also indicate corrections to stoichiometry patterns with fluorescent proteins previously in print. We also introduce properties at the single molecule level of new FRET pairs with combinations of fluorescent proteins and artificial fluorophores.