EDBT 2026 Demo / reviewers in the wild / expert
Svetlana Surkova
dblp:88/7069
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0002-9016-4732ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 67% Medical and health informatics · 33% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
deconvolution |
0.1 | 1 | 2009 | Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila · Bioinform. 2009 |
Medical and health informatics › medical imaging › medical image analysis
quantitative image analysis |
0.1 | 1 | 2009 | Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila · Bioinform. 2009 |
Methods — techniques the papers use, named apart from their topics
richardson-lucy deconvolution · 0.1censoring technique · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Modeling of Gap Gene Expression in Drosophila Kruppel MutantsabstractThe segmentation gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of gene expression, which determines both the positions and the identities of body segments. The gap gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of gap gene Kruppel (Kr) on segmentation gene expression. We acquired a large dataset on the expression of gap genes in Kr null mutants and demonstrated that the expression levels of these genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the gene circuit method which extracts regulatory information from spatial gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce gap gene expression in mutants for a trunk gap gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of gap genes in Kr null mutants. We found that the remarkable alteration of gap gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target gene and exclusion of Kr gene from the complex network of gap gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of gap gene expression in mutant for the trunk gap gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations. Konstantin Kozlov, Svetlana Surkova, Ekaterina M. Myasnikova, John Reinitz, Maria Samsonova |
PLoS Comput. Biol. | 2 |
| 2011 | A regression system for estimation of errors introduced by confocal imaging into gene expression data in situabstractBACKGROUND: Accuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images. For the estimation and correction of this kind of errors a method based on censoring technique (Myasnikova et al., 2009) is used. However, the method requires the availability of all the confocal scans along with the averaged image, which is normally not provided by the standard scanning procedure. RESULTS: To predict error size in the data extracted from the averaged image we developed a regression system. The system is trained on the learning sample composed of images obtained from three different microscopes at different combinations of PMT parameters, and for each image all the scans are saved. The system demonstrates high prediction accuracy and was applied for correction of errors in the data on segmentation gene expression in Drosophila blastoderm stored in the FlyEx database (http://urchin.spbcas.ru/flyex/, http://flyex.uchicago.edu/flyex/). The prediction method is realized as a software tool CorrectPattern freely available at http://urchin.spbcas.ru/asp/2011/emm/. CONCLUSIONS: We created a regression system and software to predict the magnitude of errors in the data obtained from a confocal image based on information about microscope parameters used for the image acquisition. An important advantage of the developed prediction system is the possibility to accurately correct the errors in data obtained from strongly clipped images, thereby allowing to obtain images of the higher dynamical range and thus to extract more detailed quantitative information from them. Ekaterina M. Myasnikova, Svetlana Surkova, Grigory Stein, Andrei Pisarev, Maria Samsonova |
BMC Bioinform. | 2 |
| 2009 | Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in DrosophilaabstractMOTIVATION: Currently the confocal scanning microscopy of fluorescently tagged molecules is extensively employed to acquire quantitative data on gene expression at cellular resolution. Following this approach, we generated a large dataset on the expression of segmentation genes in the Drosophila blastoderm, that is widely used in systems biology studies. As data accuracy is of critical importance for the success of studies in this field, we took a shot to evaluate possible errors introduced in the data by acquisition and processing methods. This article deals with errors introduced by confocal microscope. RESULTS: In confocal imaging, the inevitable photon noise is commonly reduced by the averaging of multiple frames. The averaging may introduce errors into the data, if single frames are clipped by microscope hardware. A method based on censoring technique is used to estimate and correct this type of errors. Additional source of errors is the quantification of blurred images. To estimate and correct these errors, the Richardson-Lucy deconvolution method was modified to provide the higher accuracy of data read off from blurred images of the Drosophila blastoderm. We have found that the sizes of errors introduced by confocal imaging make up approximately 5-7% of the mean intensity values and do not disguise the dynamic behavior and characteristic features of gene expression patterns. We also defined a range of microscope parameters for the acquisition of sufficiently accurate data. AVAILABILITY: http://urchin.spbcas.ru/downloads/step/step.htm Ekaterina M. Myasnikova, Svetlana Surkova, Lena Panok, Maria Samsonova, John Reinitz |
Bioinform. | 2 |
| 2009 | Canalization of Gene Expression and Domain Shifts in the Drosophila Blastoderm by Dynamical AttractorsabstractThe variation in the expression patterns of the gap genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.pbio.1000049). This biologically essential process is an example of the phenomenon known as canalization. It has been suggested that the developmental trajectory of a wild-type organism is inherently stable, and that canalization is a manifestation of this property. Although the role of gap genes in the canalization process was established by correctly predicting the response of the system to particular perturbations, the stability of the developmental trajectory remains to be investigated. For many years, it has been speculated that stability against perturbations during development can be described by dynamical systems having attracting sets that drive reductions of volume in phase space. In this paper, we show that both the reduction in variability of gap gene expression as well as shifts in the position of posterior gap gene domains are the result of the actions of attractors in the gap gene dynamical system. Two biologically distinct dynamical regions exist in the early embryo, separated by a bifurcation at 53% egg length. In the anterior region, reduction in variation occurs because of stability induced by point attractors, while in the posterior, the stability of the developmental trajectory arises from a one-dimensional attracting manifold. This manifold also controls a previously characterized anterior shift of posterior region gap domains. Our analysis shows that the complex phenomena of canalization and pattern formation in the Drosophila blastoderm can be understood in terms of the qualitative features of the dynamical system. The result confirms the idea that attractors are important for developmental stability and shows a richer variety of dynamical attractors in developmental systems than has been previously recognized. Manu, Svetlana Surkova, Alexander V. Spirov, Vitaly V. Gursky, Hilde Janssens, Ah-Ram Kim, Ovidiu Radulescu, Carlos E. Vanario-Alonso, David H. Sharp, Maria Samsonova, John Reinitz |
PLoS Comput. Biol. | 2 |