The Experience Software-based Design of Virtual Medical Intrascopy Systems for Simulation Study

The questions of software-based design of “virtual” technical systems are considered as facility of imitation experiment for educational purposes. These virtual systems are usable for analysis of medical intrascopy systems functioning. The virtual educational technical systems allow guarantee the goodness technical training of bioengineers

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging

How to predict gene function from phenotypic cues is a longstanding question in biology.Using quantitative multiparametric imaging, RNAi-mediated cell phenotypes were measured on a genome-wide scale.On the basis of phenotypic ‘neighbourhoods', we identified previously uncharacterized human genes as mediators of the DNA damage response pathway and the maintenance of genomic integrity.The phenotypic map is provided as an online resource at http://www.cellmorph.org for discovering further functional relationships for a broad spectrum of biological modul

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. Results We present a free, open-source R package Ringo that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions. Conclusion Ringo integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It facilitates the construction of programmed analysis workflows, offers benefits in scalability, reproducibility and methodical scope of the analyses and opens up a broad selection of follow-up statistical and bioinformatic methods.</p

"Flora of Russia" on iNaturalist: a dataset

The "Flora of Russia" project on iNaturalist brought together professional scientists and amateur naturalists from all over the country. Over 10,000 people are involved in the data collection.Within 20 months the participants accumulated over 750,000 photo observations of 6,853 species of the Russian flora. This constitutes the largest dataset of open spatial data on the country’s biodiversity and a leading source of data on the current state of the national flora. About 85% of all project data are available under free licenses (CC0, CC-BY, CC-BY-NC) and can be freely used in scientific, educational and environmental activities

"Flora of Russia" on iNaturalist: a dataset

The "Flora of Russia" project on iNaturalist brought together professional scientists and amateur naturalists from all over the country. Over 10,000 people are involved in the data collection.Within 20 months the participants accumulated over 750,000 photo observations of 6,853 species of the Russian flora. This constitutes the largest dataset of open spatial data on the country’s biodiversity and a leading source of data on the current state of the national flora. About 85% of all project data are available under free licenses (CC0, CC-BY, CC-BY-NC) and can be freely used in scientific, educational and environmental activities

"Flora of Russia" on iNaturalist: a dataset

The "Flora of Russia" project on iNaturalist brought together professional scientists and amateur naturalists from all over the country. Over 10,000 people are involved in the data collection.Within 20 months the participants accumulated over 750,000 photo observations of 6,853 species of the Russian flora. This constitutes the largest dataset of open spatial data on the country’s biodiversity and a leading source of data on the current state of the national flora. About 85% of all project data are available under free licenses (CC0, CC-BY, CC-BY-NC) and can be freely used in scientific, educational and environmental activities