Oleg Sklyar

Bio: Oleg Sklyar is an academic researcher from University of Oldenburg. The author has contributed to research in topics: Scanning electrochemical microscopy & Bioconductor. The author has an hindex of 9, co-authored 10 publications receiving 1039 citations. Previous affiliations of Oleg Sklyar include European Bioinformatics Institute.

EBImage—an R package for image processing with applications to cellular phenotypes

Abstract: Summary: EBImage provides general purpose functionality for reading, writing, processing and analysis of images. Furthermore, in the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization. Availability: EBImage is free and open source, released under the LGPL license and available from the Bioconductor project (http://www.bioconductor.org/packages/release/bioc/html/EBImage.html). Contact: gregoire.pau/at/ebi.ac.uk

Ringo--an R/Bioconductor package for analyzing ChIP-chip readouts.

Abstract: Background Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modifications. However, the raw microarray intensity readings themselves are not immediately useful to researchers, but require a number of bioinformatic analysis steps. Identified enriched regions need to be bioinformatically annotated and compared to related datasets by statistical methods.

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Abstract: Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.

Numerical simulations of complex nonsymmetrical 3D systems for scanning electrochemical microscopy using the boundary element method

Abstract: Quantitative treatment of the problems related to scanning electrochemical microscopy (SECM) is performed by means of numerical simulations using the boundary element method (BEM). The method is used to calculate the amperometric steady-state response of a microelectrode or nanoelectrode of a given arbitrary geometry in the SECM feedback mode above surfaces with ideal negative feedback or diffusion-controlled positive feedback. By changing the problem setup from the interior to the exterior Laplace formalism, the precision of the calculation could be improved significantly because the exterior formulation does not require any assumptions about the extension of the diffusion layer at infinite time. The improved precision was demonstrated by simulations of standard problems that have been treated before by finite difference methods. Subsequently a series of simulations is presented that explores the effects of deviations from idealized SECM geometries used in many available finite difference simulations. Su...

Numerical Simulation of Scanning Electrochemical Microscopy Experiments with Frame-Shaped Integrated Atomic Force Microscopy−SECM Probes Using the Boundary Element Method

Abstract: Integrated submicroelectrodes for combined AFM−SECM measurements are characterized with numerical simulations using the boundary element method. SECM approach curves and SECM images are calculated and analyzed for a model substrate containing pronounced topographical and electrochemical features. The theoretically calculated image has been compared to the experimental data and shows excellent quantitative agreement. Hence, the applicability of integrated AFM−SECM electrodes for combined electrochemical and topographical imaging and a profound theoretical description including quantification of the obtained results are demonstrated.

ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data

Abstract: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome. We have developed ChIPpeakAnno as a Bioconductor package within the statistical programming environment R to facilitate batch annotation of enriched peaks identified from ChIP-seq, ChIP-chip, cap analysis of gene expression (CAGE) or any experiments resulting in a large number of enriched genomic regions. The binding sites annotated with ChIPpeakAnno can be viewed easily as a table, a pie chart or plotted in histogram form, i.e., the distribution of distances to the nearest genes for each set of peaks. In addition, we have implemented functionalities for determining the significance of overlap between replicates or binding sites among transcription factors within a complex, and for drawing Venn diagrams to visualize the extent of the overlap between replicates. Furthermore, the package includes functionalities to retrieve sequences flanking putative binding sites for PCR amplification, cloning, or motif discovery, and to identify Gene Ontology (GO) terms associated with adjacent genes. ChIPpeakAnno enables batch annotation of the binding sites identified from ChIP-seq, ChIP-chip, CAGE or any technology that results in a large number of enriched genomic regions within the statistical programming environment R. Allowing users to pass their own annotation data such as a different Chromatin immunoprecipitation (ChIP) preparation and a dataset from literature, or existing annotation packages, such as GenomicFeatures and BSgenom e, provides flexibility. Tight integration to the biomaRt package enables up-to-date annotation retrieval from the BioMart database.

Scanning electrochemical microscopy

Abstract: A new scanning electrochemical microscopy tip positioning method that allows topography and surface activity to be resolved independently is presented. A SECM tip is oscillated relative to the surface of interest. Changes in the oscillation amplitude, caused by the intermittent contact of the SECM tip with the surface of interest, are used to detect the surface of interest, and as a feedback signal for various types of imaging.

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

Abstract: In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, which is a morphological profiling assay that multiplexes six fluorescent dyes, imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multiwell plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Next, an automated image analysis software identifies individual cells and measures ∼1,500 morphological features (various measures of size, shape, texture, intensity, and so on) to produce a rich profile that is suitable for the detection of subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes 2 weeks; feature extraction and data analysis take an additional 1-2 weeks.

Biological imaging software tools

Abstract: Representative members of the bioimage informatics community review the computational steps and some of the primary software tools available to biologists who are acquiring and analyzing microscopy-based digital image data, with a focus on open-source options. Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.