1,384 resources related to Proteomics
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The world's premiere conference in MEMS sensors, actuators and integrated micro and nano systems welcomes you to attend this four-day event showcasing major technological, scientific and commercial breakthroughs in mechanical, optical, chemical and biological devices and systems using micro and nanotechnology.The major areas of activity in the development of Transducers solicited and expected at this conference include but are not limited to: Bio, Medical, Chemical, and Micro Total Analysis Systems Fabrication and Packaging Mechanical and Physical Sensors Materials and Characterization Design, Simulation and Theory Actuators Optical MEMS RF MEMS Nanotechnology Energy and Power
The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore
The conference is the primary forum for cross-industry and multidisciplinary research in automation. Its goal is to provide a broad coverage and dissemination of foundational research in automation among researchers, academics, and practitioners.
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2019, the 26th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.
Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, 2009
Shotgun proteomics has emerged as a powerful technology for protein identification with remarkable applications in discovering disease biomarkers. Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong ...
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
Protein identification using mass spectrometry is a critical step in many areas of the life sciences, and in proteomics in particular. To confirm the presence of a protein in a sample, at least one of the constituent peptides from that protein must be matched to a theoretical peptide sequence. The prediction of a fragmentation spectrum from a theoretical sequence so ...
IEEE Pulse, 2017
In this paper rapid DNA analysis, proteomics, and new technology increasingly impact forensics investigations. It was the fast-moving technological advances in firearms, bloodstain, and other forensic analyses, as well as crime scene reconstruction, that led UNH to pursue the idea of a graduate program in forensics technology. At the same time, law enforcement agencies had begun to see the necessity ...
TRANSDUCERS 2009 - 2009 International Solid-State Sensors, Actuators and Microsystems Conference, 2009
Separations of complex proteomes are required to fractionate components before downstream identification and quantification of individual protein species. Twodimensional gels based on a combination of isoelectric focusing (IEF) and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) have been a core technology for real-word detection of thousands of proteins, and microfluidic systems which mimic the functionality of 2-D gels in a ...
2018 IEEE 14th International Conference on e-Science (e-Science), 2018
Numerous software utilities operating on mass spectrometry (MS) data are described in the literature that provide specific operations as building blocks for the assembly of purpose-specific workflows. Working out which tools and combinations are applicable or optimal is often hard: insufficient annotation of tool functions and interfaces impedes finding viable tool combinations, and potentially compatible tools may not, in practice, ...
Shotgun proteomics has emerged as a powerful technology for protein identification with remarkable applications in discovering disease biomarkers. Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence (confident proteins) are reported, while many possible proteins of potential biological interest are eliminated. In biomarker studies, this conservative assembly may prevent us from identifying important biomarker candidates. In this study, we have developed a protein interaction network-assisted complex-enrichment approach (CEA) to improve protein identification by taking into consideration the functional relationship among proteins as embedded in protein interaction networks. CEA is based on the assumption that an eliminated protein is more likely to be present in the original sample if it is a member of a complex for which other members have been confidently identified in the same sample.
Protein identification using mass spectrometry is a critical step in many areas of the life sciences, and in proteomics in particular. To confirm the presence of a protein in a sample, at least one of the constituent peptides from that protein must be matched to a theoretical peptide sequence. The prediction of a fragmentation spectrum from a theoretical sequence so that it can be compared to an observed spectrum is the key challenge of protein identification algorithms. We present a study using artificial neural networks to learn properties of fragmentation spectra so that more peptides and therefore proteins can be identified in high-throughput proteomics.
In this paper rapid DNA analysis, proteomics, and new technology increasingly impact forensics investigations. It was the fast-moving technological advances in firearms, bloodstain, and other forensic analyses, as well as crime scene reconstruction, that led UNH to pursue the idea of a graduate program in forensics technology. At the same time, law enforcement agencies had begun to see the necessity of specially trained individuals who understand the capabilities and limitations of the technologies and can put them to best use. UNH spent three years on curriculum development and added four new faculty members and about US$1 million worth of high-tech equipment to get the program going. The first class in its forensics technology master of science program graduated in May 2017.
Separations of complex proteomes are required to fractionate components before downstream identification and quantification of individual protein species. Twodimensional gels based on a combination of isoelectric focusing (IEF) and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) have been a core technology for real-word detection of thousands of proteins, and microfluidic systems which mimic the functionality of 2-D gels in a miniature high-throughput format are a promising technology. Here we describe a new approach based on the combination of IEF with parallel capillary zone electrophoresis (CZE) in a microchip format, enabling improved reproducibility and higher throughput separations by eliminating the use of sieving gel in the second separation dimension. Although the system sacrifices some degree of resolving power through the use of non-orthogonal separation modes, overall peak capacities on the order of 2,500 are realized in the 2-D microfluidic chips.
Numerous software utilities operating on mass spectrometry (MS) data are described in the literature that provide specific operations as building blocks for the assembly of purpose-specific workflows. Working out which tools and combinations are applicable or optimal is often hard: insufficient annotation of tool functions and interfaces impedes finding viable tool combinations, and potentially compatible tools may not, in practice, operate together. Thus researchers face difficulties in selecting practical and effective data analysis pipelines for a specific experimental design.
Proteomics, the study of all the proteins contained in a particular sample, e.g., a cell, is a key technology in current biomedical research. The complexity and volume of proteomics data sets produced by mass spectrometric methods clearly suggests the use of grid-based high-performance computing for analysis. TOPP and OpenMS are open-source packages for proteomics data analysis, however, they do not provide support for Grid computing. In this work we present a portal interface for high-throughput data analysis with TOPP. The portal is based on Rapid, a tool for efficiently generating standardized port lets for a wide range of applications. The web-based interface allows the creation and editing of user-defined pipelines and their execution and monitoring on a Grid infrastructure. The portal also supports several file transfer protocols for data staging. It thus provides a simple and complete solution to high-throughput proteomics data analysis for inexperienced users through a convenient portal interface.
Sumamry form only given. The word “omics” indicates the study of a total information in biological cell, such as the genome, which is all DNA in a living cell, or the proteome which is all the proteins. Omics technologies of genomics and proteomics, such as tailor-made treatment, it has been positioned in the center of the future of medical technology. The efficiency of this technology is also expected by microwave technology. Microwave technology, for the time shortening of omics pretreatment reaction, has been fully achieved. The corresponding to the small-scale is also strongly desired to high- throughput technology such as a well plate. The corresponding to the small- scale is strongly desired to high-throughput technology such as a well plate. In this study, we tried the microwave assisted proteomics for enzymatic hydrolysis of protein molecules with a protease tripsin. Chicken egg white- derived lysozyme having a molecular weight 14,300 as a model protein was used in the enzymatic hydrolysis. The molar ratio of trypsin and lysozyme was adjusted to 1 : 50, reductive alkylation lysozyme was digested with 37°C, and analyzed by MALDI-TOF MS after the reaction. An irradiation reactor of cavity resonator type was applied to enzyme reaction microwaves continuously irradiated with microwaves of 16 W, and maintained at 37°C, of the reaction temperature. The conventional method was used with a water bath. As a result, reaction time was reduced from 20 hours to 10 minutes. It was found that the reaction had proceeded completely, from Mass spectrum. In the enzymatic hydrolysis, there is the problems to digest for oneself. However, the autolysis of trypsin under microwave irradiation was not detected. Next, we had checked by MASCOT searching after TOFMS analysis, it was confirmed which part of the protein is cleaved from the protein fragments. Enzyme-substrate concentration, time of 1 to 10, the sequence coverage of 84% by microwave irradiation was 57% under normal conditions. Trypsin recognized amino acid sequence, which means that 84% is broken, it was considered to cleave amino acid residues inside the protein.
The high occurrence rate of the cardiovascular diseases and the development of proteomics bring the cardio-muscle proteomics. All have already opened a related research one after another at home and abroad currently, but almost of these focuses on the cardiovascular disease, few on sports science. According to the importance of heat in sports, applying cardio-muscle proteomics on sports science is very significant, because it can study the influence of exercise stimulation imposing on cardio muscle proteome during the whole process. According to the present condition, sum up all the known myocardial proteins and give them a classification, sum up the study of myocardial proteins in sports science, sum up and the main problems of the methods and protocols of cardio-muscle proteomics, and put forward the research and the applied foreground of cardio-muscle proteomics in sports science, to provide a reference for workers to study cardio-muscle proteome.
The Gene Ontology Consortium built the Gene Ontology database (GO) to address the need for a common standard in naming genes and gene products. Using different names for the same concepts and different concepts with the same name makes it effectively impossible for humans and computers alike to analyze biological processes across different organisms. The consortium addresses this need by defining terms for categorizing genes and gene products. A convention in GO is that each gene or gene product is annotated to the most specific GO term in the GO database. It is, however, also useful for researchers to be able to group genesor gene products into broad biological categories that give a higher-level view of their function when analyzing results of an experiment. A GO Slim is a subset of the GO ontology that provides such a higher-level view of functions. Existing GO Slim generation tools have two important limitations: programming language dependence, and an inability to dynamically generate a GO Slim while analyzing. We have extended the relational database engine to dynamically generate a GO Slim overcoming this limitations. Using this extension, we have developed a tool (Dynamic GOSlim) that dynamically generates a GO Slim and uses the generated GO Slim to categorize genes or gene products. This tool is being used in an ongoing proteomics project aimed at identifying possible oral cancer biomarkers in saliva.
Advances in mass spectrometry-based proteomics have brought expectations for biomedical researchers. It can be used for identify proteomic patterns in body fluids to discriminate patients from control, the results are inspiring. However, most of the earlier studies are based on the direct application of original MS data, together with dimension reduction or feature selection methods. We deemed that only the peaks of MS data have real biological meaning, so it's important to obtain the ultimate proteomic pattern using the real peaks. In this paper, we proposed a workflow that combined wavelet transform, statistical analysis and decision tree learning to process MS data. Especially, the statistical analysis which have not been attached too much importance in most studies was investigated, the possible distribution law of the MS peaks was proposed.
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