Relevant bibliographies by topics / Automated cell to signal

Academic literature on the topic 'Automated cell to signal'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Automated cell to signal"

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Frank, Tino, and Savaş Tay. "Automated co-culture system for spatiotemporal analysis of cell-to-cell communication." Lab on a Chip 15, no. 10 (2015): 2192–200. http://dx.doi.org/10.1039/c5lc00182j.

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Bußmann, Agnes, Thomas Thalhofer, Sophie Hoffmann, Leopold Daum, Nivedha Surendran, Oliver Hayden, Jürgen Hubbuch, and Martin Richter. "Microfluidic Cell Transport with Piezoelectric Micro Diaphragm Pumps." Micromachines 12, no. 12 (November 27, 2021): 1459. http://dx.doi.org/10.3390/mi12121459.

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The automated transport of cells can enable far-reaching cell culture research. However, to date, such automated transport has been achieved with large pump systems that often come with long fluidic connections and a large power consumption. Improvement is possible with space- and energy-efficient piezoelectric micro diaphragm pumps, though a precondition for a successful use is to enable transport with little to no mechanical stress on the cell suspension. This study evaluates the impact of the microfluidic transport of cells with the piezoelectric micro diaphragm pump developed by our group. It includes the investigation of different actuation signals. Therewith, we aim to achieve optimal fluidic performance while maximizing the cell viability. The investigation of fluidic properties proves a similar performance with a hybrid actuation signal that is a rectangular waveform with sinusoidal flanks, compared to the fluidically optimal rectangular actuation. The comparison of the cell transport with three actuation signals, sinusoidal, rectangular, and hybrid actuation shows that the hybrid actuation causes less damage than the rectangular actuation. With a 5% reduction of the cell viability it causes similar strain to the transport with sinusoidal actuation. Piezoelectric micro diaphragm pumps with the fluidically efficient hybrid signal actuation are therefore an interesting option for integrable microfluidic workflows.
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KRISHNAN, M. MUTHU RAMA, S. VINITHA SREE, DHANJOO N. GHISTA, EDDIE Y. K. NG, SWAPNA, ALVIN P. C. ANG, KWAN-HOONG NG, and JASJIT S. SURI. "AUTOMATED DIAGNOSIS OF CARDIAC HEALTH USING RECURRENCE QUANTIFICATION ANALYSIS." Journal of Mechanics in Medicine and Biology 12, no. 04 (September 2012): 1240014. http://dx.doi.org/10.1142/s0219519412400143.

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The sum total of millions of cardiac cell depolarization potentials can be represented using an electrocardiogram (ECG). By inspecting the P-QRS-T wave in the ECG of a patient, the cardiac health can be diagnosed. Since the amplitude and duration of the ECG signal are too small, subtle changes in the ECG signal are very difficult to be deciphered. In this work, the heart rate variability (HRV) signal has been used as the base signal to observe the functioning of the heart. The HRV signal is non-linear and non-stationary. Recurrence quantification analysis (RQA) has been used to extract the important features from the heart rate signals. These features were fed to the fuzzy, Gaussian mixture model (GMM), and probabilistic neural network (PNN) classifiers for automated classification of cardiac bio-electrical contractile disorders. Receiver operating characteristics (ROC) was used to test the performance of the classifiers. In our work, the Fuzzy classifier performed better than the other classifiers and demonstrated an average classification accuracy, sensitivity, specificity, and positive predictive value of more than 83%. The developed system is suitable to evaluate large datasets.
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Francis, Michael, Xun Qian, Chimène Charbel, Jonathan Ledoux, J. C. Parker, and Mark S. Taylor. "Automated region of interest analysis of dynamic Ca2+ signals in image sequences." American Journal of Physiology-Cell Physiology 303, no. 3 (August 1, 2012): C236—C243. http://dx.doi.org/10.1152/ajpcell.00016.2012.

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Ca2+ signals are commonly measured using fluorescent Ca2+ indicators and microscopy techniques, but manual analysis of Ca2+ measurements is time consuming and subject to bias. Automated region of interest (ROI) detection algorithms have been employed for identification of Ca2+ signals in one-dimensional line scan images, but currently there is no process to integrate acquisition and analysis of ROIs within two-dimensional time lapse image sequences. Therefore we devised a novel algorithm for rapid ROI identification and measurement based on the analysis of best-fit ellipses assigned to signals within noise-filtered image sequences. This algorithm was implemented as a plugin for ImageJ software (National Institutes of Health, Bethesda, MD). We evaluated the ability of our algorithm to detect synthetic Gaussian signal pulses embedded in background noise. The algorithm placed ROIs very near to the center of a range of signal pulses, resulting in mean signal amplitude measurements of 99.06 ± 4.11% of true amplitude values. As a practical application, we evaluated both agonist-induced Ca2+ responses in cultured endothelial cell monolayers, and subtle basal endothelial Ca2+ dynamics in opened artery preparations. Our algorithm enabled comprehensive measurement of individual and localized cellular responses within cultured cell monolayers. It also accurately identified characteristic Ca2+ transients, or Ca2+ pulsars, within the endothelium of intact mouse mesenteric arteries and revealed the distribution of this basal Ca2+ signal modality to be non-Gaussian with respect to amplitude, duration, and spatial spread. We propose that large-scale statistical evaluations made possible by our algorithm will lead to a more efficient and complete characterization of physiologic Ca2+-dependent signaling.
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Wenus, Jakub, Heiko Düssmann, Perrine Paul, Dimitrios Kalamatianos, Markus Rehm, Peter E. Wellstead, Jochen H. M. Prehn, and Heinrich J. Huber. "ALISSA: an automated live-cell imaging system for signal transduction analyses." BioTechniques 47, no. 6 (December 2009): 1033–40. http://dx.doi.org/10.2144/000113247.

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Khandekar, Rohan, Prakhya Shastry, Smruthi Jaishankar, Oliver Faust, and Niranjana Sampathila. "Automated blast cell detection for Acute Lymphoblastic Leukemia diagnosis." Biomedical Signal Processing and Control 68 (July 2021): 102690. http://dx.doi.org/10.1016/j.bspc.2021.102690.

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Shen, Hailin, Glyn Nelson, David E. Nelson, Stephnie Kennedy, David G. Spiller, Tony Griffiths, Norman Paton, Stephen G. Oliver, Michael R. H. White, and Douglas B. Kell. "Automated tracking of gene expression in individual cells and cell compartments." Journal of The Royal Society Interface 3, no. 11 (June 14, 2006): 787–94. http://dx.doi.org/10.1098/rsif.2006.0137.

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Many intracellular signal transduction processes involve the reversible translocation from the cytoplasm to the nucleus of transcription factors. The advent of fluorescently tagged protein derivatives has revolutionized cell biology, such that it is now possible to follow the location of such protein molecules in individual cells in real time. However, the quantitative analysis of the location of such proteins in microscopic images is very time consuming. We describe CellTracker, a software tool designed for the automated measurement of the cellular location and intensity of fluorescently tagged proteins. CellTracker runs in the MS Windows environment, is freely available (at http://www.dbkgroup.org/celltracker/ ), and combines automated cell tracking methods with powerful image-processing algorithms that are optimized for these applications. When tested in an application involving the nuclear transcription factor NF-κB, CellTracker is competitive in accuracy with the manual human analysis of such images but is more than 20 times faster, even on a small task where human fatigue is not an issue. This will lead to substantial benefits for time-lapse-based high-content screening.
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Skinner, Benjamin Matthew, Joanne Bacon, Claudia Cattoni Rathje, Erica Lee Larson, Emily Emiko Konishi Kopania, Jeffrey Martin Good, Nabeel Ahmed Affara, and Peter James Ivor Ellis. "Automated Nuclear Cartography Reveals Conserved Sperm Chromosome Territory Localization across 2 Million Years of Mouse Evolution." Genes 10, no. 2 (February 1, 2019): 109. http://dx.doi.org/10.3390/genes10020109.

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Measurements of nuclear organization in asymmetric nuclei in 2D images have traditionally been manual. This is exemplified by attempts to measure chromosome position in sperm samples, typically by dividing the nucleus into zones, and manually scoring which zone a fluorescence in-situ hybridisation (FISH) signal lies in. This is time consuming, limiting the number of nuclei that can be analyzed, and prone to subjectivity. We have developed a new approach for automated mapping of FISH signals in asymmetric nuclei, integrated into an existing image analysis tool for nuclear morphology. Automatic landmark detection defines equivalent structural regions in each nucleus, then dynamic warping of the FISH images to a common shape allows us to generate a composite of the signal within the entire cell population. Using this approach, we mapped the positions of the sex chromosomes and two autosomes in three mouse lineages (Mus musculus domesticus, Mus musculus musculus and Mus spretus). We found that in all three, chromosomes 11 and 19 tend to interact with each other, but are shielded from interactions with the sex chromosomes. This organization is conserved across 2 million years of mouse evolution.
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Li, Stephen K. H., Nick Zabinyakov, Alexandre Bouzekri, Rita Straus, Raymond Jong, Michael Sullivan, Alexander Loboda, Daniel Majonis, and Christina Loh. "An automated approach to high-plex cytometric immunophenotyping with CyTOF XT." Journal of Immunology 208, no. 1_Supplement (May 1, 2022): 172.17. http://dx.doi.org/10.4049/jimmunol.208.supp.172.17.

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Abstract CyTOF® mass cytometry is a single-cell analysis platform that uses isotope-tagged antibodies to resolve 50-plus markers in a single tube without signal compensation, making CyTOF ideal for routine immunophenotyping. CyTOF XT™, the latest CyTOF system, features automated sample acquisition. Stained samples were acquired in parallel using the automated CyTOF XT system and manually, using the Helios™ system, to assess performance of the automated system. Multiple suspension mass cytometry staining workflows were evaluated. Population frequencies and resolution indices for markers were assessed by manual gating. There was no significant difference between population frequencies analyzed between the two CyTOF systems. On average, samples acquired on CyTOF XT resulted in greater resolution between positive and negative populations compared to Helios. The Maxpar® Direct™ Immune Profiling System, which comprises the Maxpar® Direct™ Immune Profiling Assay™ and Maxpar Pathsetter™ software, was also compared on the CyTOF XT and Helios systems. The Maxpar Direct Immune Profiling Assay includes a 30-marker panel in a dry, single-tube format for staining human whole blood or PBMC. Maxpar Pathsetter automates reporting of population statistics and stain assessments for the panel. Maxpar Pathsetter showed comparable population frequencies between the two CyTOF systems and improved staining assessment on CyTOF XT. Overall, these studies find that the CyTOF XT system generates better signal resolution than the Helios system. Automated acquisition by CyTOF XT enables researchers to accurately and reproducibly streamline human immunophenotyping. For Research Use Only. Not for use in diagnostic procedures.
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Meyer, Michael G., Mark Fauver, J. Richard Rahn, Thomas Neumann, Florence W. Patten, Eric J. Seibel, and Alan C. Nelson. "Automated cell analysis in 2D and 3D: A comparative study." Pattern Recognition 42, no. 1 (January 2009): 141–46. http://dx.doi.org/10.1016/j.patcog.2008.06.018.

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Dissertations / Theses on the topic "Automated cell to signal"

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Taylor, Harriet Beverly. "Functional analysis of zebrafish innate immune responses to inflammatory signals." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4825.

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Injury, infection and tissue malfunction are triggers of inflammation which if not regulated may acquire new characteristics that result in pathological outcomes. Since innate immunity plays a key role in the resolution of acute inflammation knowledge of the regulation of this component of the host response is relevant to understanding processes in disease progression and therefore has potential clinical benefits. In this thesis I have applied zebrafish as a model organism to investigate the response of innate immune cells to qualitatively distinct inflammatory signals in the absence of adaptive immunity. Using a zebrafish embryo wound injury model I have investigated leukocyte migration profiles by in vivo imaging. In response to wound alone leukocytes migrated to the site of injury with predominantly random walk behaviour. However, the addition of lipopolysaccharide (LPS) enhanced recruitment and influenced the directionality of leukocyte migration to the wound. I demonstrate that leukocyte dynamic behaviour is also dependent on the location of the cells. The LPS enhanced directionality and reduced the random walk behaviour of the leukocytes, and these effects were ablated in the presence of the p38 mitogenactivated protein kinase (MAPK) specific inhibitor SB203580. Cytokine gene profiling in adult zebrafish leukocytes reveals that LPS can stimulate a pro-inflammatory response via the activation of p38 MAPK characteristic of mammalian innate immune responses. It is documented in mammalian innate immune cells that LPS can modulate Notch mediated signalling and thereby cell function. Using zebrafish with null mutations in Notch, which provide an unbiased in vivo model, I have investigated the influence of Notch signalling on leukocyte recruitment and demonstrate that migration to a wound injury is reduced. However, this effect is due to decreased cell numbers and not altered function as the Notch signalling inhibitor DAPT had no effect of recruitment to wound injury. The defect in myelomonocyte numbers was also present in adult zebrafish and this was partially compensated for by an increase in lymphocytes. The experimental results that I report here highlight zebrafish as a model 2 organism for studying the function and regulation of innate immunity. The unique optical translucency, which permits in vivo imaging of host responses in real-time, facilitates the analysis of the innate immune response to different inflammatory signals and immune modulators.
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O'Neill, Kieran. "Automated analysis of single cell leukemia data." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50867.

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Acute myeloid leukemia (AML) is a high grade malignancy of non-lymphoid cells of the hematopoietic system. AML is a heterogeneous disease, and numerous attempts have been made to risk-stratify AML so that appropriate treatment can be offered. Single cell analysis methods could provide insights into the biology of AML leading to risk-stratified and functionally tailored treatments and hence improved outcomes. Recent advances in flow cytometry allow the simultaneous measurement of up to 17 antibody markers per cell for up to millions of cells, and it is performed routinely during AML clinical workup. However, despite vast amounts of flow cytometry data being gathered, comprehensive, objective and automated studies of this data have not been undertaken. Another method, strand-seq, elucidates template strand inheritance in single cells, with a range of potential applications, none of which had been automated when this thesis work commenced. I have developed bioinformatic methods enabling research into AML using both these types of data. I present flowBin, a method for faithfully recombining multitube flow cytometry data. I present flowType-DP, a new version of flowType, able to process flow cytometry and other single cell data having more than 12 markers (including flowBin output). I demonstrate the application of flowBin to AML data, for digitally isolating abnormal cells, and classifying AML patients. I also use flowBin in conjunction with flowType to find cell types associated with clinically relevant gene mutations in AML. I present BAIT, a software package for accurately detecting sister chromatid exchanges in strand-seq data. I present functionality to place unbridged contigs in late-build genomes into their correct location, and have, with collaborators, published the corrected locations of more than half the unplaced contigs in the current build of the mouse genome. I present contiBAIT, a software package for assembling early-build genomes which consist entirely of unanchored, unbridged contigs. ContiBAIT has the potential to dramatically improve the quality of many model organism genomes at low cost. These developments enable rapid, automated, objective and reproducible deep profiling of AML flow cytometry data, subclonal cell analysis of AML cytogenetics, and improvements to model organisms used in AML research.
Science, Faculty of
Graduate
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Martin, Bailey-Van Kuren Michael. "Automated cell supervisory control for product disassembly." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/20158.

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Balraj, Navaneethakrishnan. "AUTOMATED ACCIDENT DETECTION IN INTERSECTIONS VIA DIGITAL AUDIO SIGNAL PROCESSING." MSSTATE, 2003. http://sun.library.msstate.edu/ETD-db/theses/available/etd-10212003-102715/.

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The aim of this thesis is to design a system for automated accident detection in intersections. The input to the system is a three-second audio signal. The system can be operated in two modes: two-class and multi-class. The output of the two-class system is a label of ?crash? or ?non-crash?. In the multi-class system, the output is the label of ?crash? or various non-crash incidents including ?pile drive?, ?brake?, and ?normal-traffic? sounds. The system designed has three main steps in processing the input audio signal. They are: feature extraction, feature optimization and classification. Five different methods of feature extraction are investigated and compared; they are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstrum transform and Mel frequency cepstral transform. Linear discriminant analysis (LDA) is used to optimize the features obtained in the feature extraction stage by linearly combining the features using different weights. Three types of statistical classifiers are investigated and compared: the nearest neighbor, nearest mean, and maximum likelihood methods. Data collected from Jackson, MS and Starkville, MS and the crash signals obtained from Texas Transportation Institute crash test facility are used to train and test the designed system. The results showed that the wavelet based feature extraction method with LDA and maximum likelihood classifier is the optimum design. This wavelet-based system is computationally inexpensive compared to other methods. The system produced classification accuracies of 95% to 100% when the input signal has a signal-to-noise-ratio of at least 0 decibels. These results show that the system is capable of effectively classifying ?crash? or ?non-crash? on a given input audio signal.
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Sameeuddin, Sameeuddin. "Automated Ultrasonic Signal Classification of Carbon Fiber Reinforced Plastic Laminates." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1497.

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Carbon composites, particularly carbon fiber reinforced plastics (CFRPs) are increasingly being used in many commercial applications such as automobile, aerospace, and civil infrastructures. This increase in the demand of CFRPs has led the manufacturers to research for ways of early detection and classification of defects in CFRP. This thesis work discusses the implementation of a Hopfield neural network (HNN) to automatically detect and classify defects in CFRP by ultrasonic testing (UT). Three of the most common and critical defects found in CFRP, i.e. foreign object (FO) inclusion, impact damage (ID), and porosity, were the main focus of this research. These defects were engineered into three different CFRP panels during manufacturing and were provided by an outside supplier. These panels were inspected on a standard immersion ultrasonic testing system in pulse-echo mode. One hundred time-amplitude based ultrasonic A-scan signals were recorded from the defected areas of each of the panels. Additionally, a hundred ultrasonic A-scan signals were recorded for the defect-free region of the CFRP. Signal preprocessing in terms of signal alignment is a vital process in any classification procedure as unaligned signals are prone to bad classification accuracies. Therefore, the raw A-scan signals were start-point aligned prior to any classification using cross-correlation technique. This research also focused on developing a feature extraction technique that could be used in conjunction with the HNN to classify the UT signals with high classification accuracy. A feature extraction technique based on gating technique was developed which consisted of five features, namely mean value of the signal, standard deviation of the signal, peak-to-peak amplitude value of the front wall echo (FEW), peak-to-peak amplitude value of the back wall echo (BWE), and time of flight (TOF) between FWE and BWE of each signal. Four other feature extraction techniques based on mean value of the signal, standard deviation value of the signal, fast Fourier transform (FFT), and discrete wavelet transform (DWT) were also used for the comparison and validation of results obtained by the developed feature extraction technique. The 100 signals for each category were randomly partitioned into equal-sized training and testing data sets. The partitioning was repeated for 1000 iterations, to average the results and obtain a robust estimate of the classification performance. The classification of the signals was carried out by implementing two approaches. The first approach utilized a dichotomous classification between each defect type and the non-defected region. And the second approach utilized a 4-class classification in which the defect types and the non-defected signals were classified at the same time. The results of this research showed that the classification accuracies for the 2-class problem obtained through the developed feature extraction technique exceeded 99%, which were in agreement with the results of classification obtained through the four conventional feature extraction techniques. The results of the 4-class problem obtained through the developed feature extraction technique exceeded 96% classification accuracy. For direct comparison, the results obtained from the four conventional feature extraction techniques exceeded 99% classification accuracies. Based on the results obtained, it can be concluded that the developed feature extraction technique can be used in conjunction with HNN to successfully classify defects in CFRP. With few modifications, the developed technique can be implemented to classify other types of defects in CFRP and can be implemented in different applications.
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Bala, Divya Chandrakant. "Cell Phenotype Analyzer: Automated Techniques for Cell Phenotyping using Contactless Dielectrophoresis." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71428.

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Cancer is among the leading causes of death worldwide. In 2012, there were 14 million new cases and 8.2 million cancer-related deaths worldwide. The number of new cancer cases is expected rise to 22 million within the next two decades. Most chronic cancers cannot be cured. However, if the precise cancer cell type is diagnosed at an earlier, less aggressive stage then the chance of curing the disease increases with accurate drug delivery. This work is a humble contribution to the advancement of cancer research. This work delves into biological cell phenotyping under a dielectrophoresis setup using computer vision. Dielectrophoresis is a well-known phenomenon in which dielectric particles are subjected to a non-homogeneous electric field. This work is an analytical part of a larger proposed system replete with hardware, software and microfluidics integration to achieve cancer cell characterization, separation and enrichment using contactless dielectrophoresis. To analyze the cell morphology, various detection and tracking algorithms have been implemented and tested on a diverse dataset comprising cell-separation video sequences. Other related applications like cell-counting and cell-proximity detection have also been implemented. Performances were evaluated against ground truth using metrics like precision, recall and RMS cell-count error. A detection approach using difference of Gaussian and super-pixel algorithm gave the highest average F-measure of 0.745. A nearest neighbor tracker and Kalman tracking method gave the best overall tracking performance with an average F-measure of 0.95. This combination of detection and tracking methods proved to be best suited for this dataset. A graphical user interface to automate the experimentation process of the proposed system was also designed.
Master of Science
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Sundström, Magnus. "Signal Transduction in Mast Cell Migration." Doctoral thesis, Uppsala University, Department of Genetics and Pathology, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-1474.

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Mast cells are essential effector cells in the immune system as they release several inflammatory mediators. An accumulation of mast cells has been described in inflammatory conditions such as asthma and allergic rhinitis. Increased mast cell number, in the skin and other organs, is also a characteristic in mastocytosis, a disease without an effective treatment. One explanation for the increase in mast cell number is migration of mast cells in the tissue. In our studies we utilised mast cell lines, including HMC-1; cell lines transfected with the c-kit gene; and in vitro developed mast cells.

Our aim was to characterise, two variants of the HMC-1 cell line; the signalling pathways essential for mast cell migration towards TGF-β and SCF; and the mechanism regulating mast cell accumulation in mastocytosis.

Our results help to explain inconsistent findings regarding mast cell biology when HMC-1 cells have been used as a model system. The two variants, which we name HMC-1560 and HMC-1560, 816, are used in different laboratories around the world. HMC-1560 and HMC-1560, 816 exhibited different characteristics regarding their karyotype, phenotype as well as their set of activating point mutations in the Kit receptor. Furthermore, divergent signalling pathways are of importance for mast cell migration towards TGF-β and SCF. The classical MAP kinase-signalling cascade was found to be of major relevance for TGF-β-induced migration. In contrast, this pathway had a modest impact on SCF-induced migration, which instead was highly dependent on p38 MAP kinase signalling. Finally, one mechanism for mast cell accumulation in mastocytosis appeared to be an activating point mutation in the gene for the Kit receptor. This mutation appeared to prone transfected cells and mast cell progenitors to a higher rate of migration towards SCF if compared with cells expressing wt Kit receptor.

In conclusion, our results show the importance of two different MAP kinase signalling pathways and mutations in the Kit receptor for mast cell migration induced by various types of stimuli. This knowledge helps us to understand the mechanism

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Lennartsson, Johan. "Stem Cell Factor Induced Signal Transduction." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2002. http://publications.uu.se/theses/91-554-5291-4/.

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Sundström, Magnus. "Signal transduction in mast cell migration /." Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2001. http://publications.uu.se/theses/91-554-5130-6/.

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Zou, Rui Ghosh Avijit. "Automated sensitivity analysis on spatio-temporal biochemical systems /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1565.

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Books on the topic "Automated cell to signal"

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Hancock, John T. Cell signalling. 3rd ed. Oxford: Oxford University Press, 2010.

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Hancock, John T. Cell signalling. 3rd ed. Oxford: Oxford University Press, 2010.

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Cell signalling. 3rd ed. Oxford: Oxford University Press, 2010.

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Miki, Toru. Signal transduction of cell division. Trivandrum, Kerala, India: Research Signpost, 2005.

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Van Duijn, Bert, and Anneke Wiltink, eds. Signal Transduction — Single Cell Techniques. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-80368-0.

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Duijn, Bert. Signal Transduction - Single Cell Techniques. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998.

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Cortes, J. D. Cordoba. Requirements for an automated machining cell. Manchester: UMIST, 1993.

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Cell signalling. Harlow: Longman, 1997.

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Cell signalling. 2nd ed. Oxford: Oxford University Press, 2005.

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NATO, Advanced Research Workshop on the Cell Surface in Signal Transduction (1986 Besançon France). The cell surface in signal transduction. Berlin: Springer-Verlag, 1987.

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Book chapters on the topic "Automated cell to signal"

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Wang, Jing, Jiwei Liu, Jianfei Liu, Hui Yan, and Ronghu Mao. "Automatic Cell Segmentation and Signal Detection in Fluorescent in Situ Hybridization." In Proceedings of 2018 Chinese Intelligent Systems Conference, 285–93. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2291-4_29.

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Zhang, David D. "Signal and Image Processing." In Automated Biometrics, 43–62. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4519-4_3.

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Gupta, Rajarshi, Madhuchhanda Mitra, and Jitendranath Bera. "ECG Signal Analysis." In ECG Acquisition and Automated Remote Processing, 15–49. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1557-8_2.

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Silvetti, Simone, Laura Nenzi, Ezio Bartocci, and Luca Bortolussi. "Signal Convolution Logic." In Automated Technology for Verification and Analysis, 267–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01090-4_16.

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O’Grady, P. J. "Cell Level Control." In Controlling Automated Manufacturing Systems, 75–87. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-011-7468-8_7.

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Davis, Bruce H., and Patrick W. Barnes. "Automated Cell Analysis: Principles." In Laboratory Hematology Practice, 26–32. Oxford, UK: Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781444398595.ch3.

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Thiery, Jean Paul. "Cell Adhesion in Morphogenesis." In Biological Signal Transduction, 349–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-75136-3_25.

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Marks, Friedrich, Ursula Klingmüller, and Karin Müller-Decker. "Regulation of Cell Division." In Cellular Signal Processing, 423–51. Second edition. | New York, NY: Garland Science, 2017.: Garland Science, 2017. http://dx.doi.org/10.4324/9781315165479-12.

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Brummer, Tilman, Winfried Elis, Michael Reth, and Michael Huber. "B-Cell Signal Transduction." In B Cell Protocols, 189–212. Totowa, NJ: Humana Press, 2004. http://dx.doi.org/10.1385/1-59259-796-3:189.

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Gudermann, F., P. Ziemeck, and J. Lehmann. "CeDEX: Automated Cell Density Determination." In Animal Cell Technology, 301–5. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5404-8_47.

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Conference papers on the topic "Automated cell to signal"

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Bartler, Alexander, Lukas Mauch, Bin Yang, Michael Reuter, and Liviu Stoicescu. "Automated Detection of Solar Cell Defects with Deep Learning." In 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. http://dx.doi.org/10.23919/eusipco.2018.8553025.

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Javaremi, Alireza Nejati, Charles P. Unsworth, and Euan S. Graham. "Improved cell tracking via automated removal of particulates." In 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2014. http://dx.doi.org/10.1109/isspit.2014.7300621.

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Das, Dev Kumar, Subhranil Koley, Chandan Chakraborty, and Asok Kumar Maiti. "Automated segmentation of Mitotic Cells for in vitro histological evaluation of oral squamous cell carcinoma." In 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2014. http://dx.doi.org/10.1109/isspit.2014.7300614.

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Roy, Mohendra, Junhee Lee, Geonsoo Jin, Sungkyu Seo, and Myung-Hyun Nam. "An automated cell detection algorithm for lensfree shadow imaging platform." In 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA). IEEE, 2013. http://dx.doi.org/10.1109/c2spca.2013.6749378.

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Basu, Saurav, and Scott T. Acton. "Estimation of Cell Statistics on a Cell Manifold for High Content Screening with Automated Cell Segmentation." In 2007 41st Asilomar conference on Signals, Systems and Computers (ACSSC). IEEE, 2007. http://dx.doi.org/10.1109/acssc.2007.4487556.

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Erturk, Izzet Fatih, Mehmet Alper Demir, Gozde Akar Ve, and Haluk Kulah. "Automatic Cell Counting From Microchannel Images." In 2022 30th Signal Processing and Communications Applications Conference (SIU). IEEE, 2022. http://dx.doi.org/10.1109/siu55565.2022.9864830.

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Chen, Xiaomei, Xiaofeng Meng, Bo Zhong, and Hong Ji. "A boundary scan cell insertion method for mixed signal board." In Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation, edited by Jiancheng Fang and Zhongyu Wang. SPIE, 2006. http://dx.doi.org/10.1117/12.718769.

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Cetin, Sukru Burak, Fariba D. Khameneh, Ercan Alp Serteli, Sercan Cayir, Gokhan Hatipoglu, Mustafa Kamasak, Samet Ayalti, Salar Razavi, Yakup Budancamanak, and Gulsah Ozsoy. "Automated cell segmentation and spot detection in fluorescence in situ hybridization staining to assess HER2 status in breast cancer." In 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404805.

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Gamarra, Margarita, Andres Mitre-Ortiz, and Hugo Escalante. "Automatic Cell Image Segmentation Using Genetic Algorithms." In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA). IEEE, 2019. http://dx.doi.org/10.1109/stsiva.2019.8730256.

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Zou, Ling, Jichen Yang, and Tangsen Huang. "Automatic cell phone recognition from speech recordings." In 2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2014. http://dx.doi.org/10.1109/chinasip.2014.6889318.

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Reports on the topic "Automated cell to signal"

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Bell, B. E. Automated saturated standard cell intercomparison. Edited by C. A. Deitesfeld. Office of Scientific and Technical Information (OSTI), October 1987. http://dx.doi.org/10.2172/5673945.

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Hart, Darren. Automated infrasound signal detection algorithms implemented in MatSeis - Infra Tool. Office of Scientific and Technical Information (OSTI), July 2004. http://dx.doi.org/10.2172/919172.

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Tuscano, Joseph M. Targeted Lymphoma Cell Death by Novel Signal Transduction Modifications. Fort Belvoir, VA: Defense Technical Information Center, July 2007. http://dx.doi.org/10.21236/ada503123.

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Tuscano, Joseph M. Targeted Lymphoma Cell Death by Novel Signal Transduction Modifications. Fort Belvoir, VA: Defense Technical Information Center, July 2009. http://dx.doi.org/10.21236/ada525894.

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Tuscano, Joseph M. Targeted Lymphoma Cell Death by Novel Signal Transduction Modifications. Fort Belvoir, VA: Defense Technical Information Center, July 2010. http://dx.doi.org/10.21236/ada538568.

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Tuscano, Joseph. Targeted Lymphoma Cell Death by Novel Signal Transduction Modifications. Fort Belvoir, VA: Defense Technical Information Center, July 2011. http://dx.doi.org/10.21236/ada566413.

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Peter J. Ortoleva. Automated Physico-Chemical Cell Model Development through Information Theory. Office of Scientific and Technical Information (OSTI), November 2005. http://dx.doi.org/10.2172/860659.

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Upadhyaya, B. R., and W. Yan. Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods. Office of Scientific and Technical Information (OSTI), November 1993. http://dx.doi.org/10.2172/10108326.

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Boothman, David A. Nuclear apoJ: An X-ray-inducible cell death signal. Final Report. Office of Scientific and Technical Information (OSTI), December 2003. http://dx.doi.org/10.2172/824533.

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Aziz, H. M. Abdul, Hong Wang, Stan Young, Joshua Sperling, and John Beck. Synthesis Study on Transitions in Signal Infrastructure and Control Algorithms for Connected and Automated Transportation. Office of Scientific and Technical Information (OSTI), June 2017. http://dx.doi.org/10.2172/1366412.

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