Vermicompost effect on the trace elements distribution in the luvic chernozem of the Krasnoyarsk forest-steppe

n the field experiment (2016-2018) in the conditions of the Krasnoyarsk forest-steppe the number of trace elements mobile forms were determined and the effect of soil organic matter and increasing doses of vermicompost on their distribution in luvic chernozem was studied. It is established that the studied vermicompost does not pollute the soil, which allows its widespread use in agriculture. The correlation and regression analysis obtained linear regression equations that reflect the relationship of the chemical element and organic matter in the soil after using increasing doses of vermicompost adequately. Elements with positive correlation and high significance level include Mn, Cu, Co and Zn

Collaborative workspaces for pathway curation

We present a web based visual biocuration workspace, focusing on curating detailed mechanistic pathways. It was designed as a flexible platform where multiple humans, NLP and AI agents can collaborate in real-time on a common model using an event driven API. We will use this platform for exploring disruptive technologies that can scale up biocuration such as NLP, human-computer collaboration, crowd-sourcing, alternative publishing and gamification. As a first step, we are designing a pilot to include an author-curation step into the scientific publishing, where the authors of an article create formal pathway fragments representing their discovery- heavily assisted by computer agents. We envision that this "microcuration" use-case will create an excellent opportunity to integrate multiple NLP approaches and semi-automated curation. © 2016, CEUR-WS. All rights reserved

Integrating biological pathways and genomic profiles with ChiBE 2

Cataloged from PDF version of article.Background: Dynamic visual exploration of detailed pathway information can help researchers digest and interpret complex mechanisms and genomic datasets. Results: ChiBE is a free, open-source software tool for visualizing, querying, and analyzing human biological pathways in BioPAX format. The recently released version 2 can search for neighborhoods, paths between molecules, and common regulators/targets of molecules, on large integrated cellular networks in the Pathway Commons database as well as in local BioPAX models. Resulting networks can be automatically laid out for visualization using a graphically rich, process-centric notation. Profiling data from the cBioPortal for Cancer Genomics and expression data from the Gene Expression Omnibus can be overlaid on these networks. Conclusions: ChiBE's new capabilities are organized around a genomics-oriented workflow and offer a unique comprehensive pathway analysis solution for genomics researchers

PATIKAmad: Putting microarray data into pathway context

High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA

ChiBE: interactive visualization and manipulation of BioPAX pathway models.

SUMMARY: Representing models of cellular processes or pathways in a graphically rich form facilitates interpretation of biological observations and generation of new hypotheses. Solving biological problems using large pathway datasets requires software that can combine data mapping, querying and visualization as well as providing access to diverse data resources on the Internet. ChiBE is an open source software application that features user-friendly multi-view display, navigation and manipulation of pathway models in BioPAX format. Pathway views are rendered in a feature-rich format, and may be laid out and edited with state-of-the-art visualization methods, including compound or nested structures for visualizing cellular compartments and molecular complexes. Users can easily query and visualize pathways through an integrated Pathway Commons query tool and analyze molecular profiles in pathway context. AVAILABILITY: http://www.bilkent.edu.tr/%7Ebcbi/chibe.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

PathwayMapper: A collaborative visual web editor for cancer pathways and genomic data

Motivation: While existing network visualization tools enable the exploration of cancer genomics data, most biologists prefer simplified, curated pathway diagrams, such as those featured in many manuscripts from The Cancer Genome Atlas (TCGA). These pathway diagrams typically summarize how a pathway is altered in individual cancer types, including alteration frequencies for each gene. Results: To address this need, we developed the web-based tool PathwayMapper, which runs in most common web browsers. It can be used for viewing pre-curated cancer pathways, or as a graphical editor for creating new pathways, with the ability to overlay genomic alteration data from cBioPortal. In addition, a collaborative mode is available that allows scientists to co-operate interactively on constructing pathways, with support for concurrent modifications and built-in conflict resolution. © 2017 The Author. Published by Oxford University Press. All rights reserved

Assessment of the efficiency of the local application of hemostatic drug Geprocel in the treatment of patients with deep burns

The work is based on the analysis of the treatment results of 35 patients with burn trauma (10 women and 25 men) aged 15 to 55 years who were treated in the burn department of Republican Scientific Centre of Urgent Medical Aid (RSCUMA) between 2017 and 2018. In this study, we report on the use of the hemostatic preparation Geprocel with an autodermoplasty on a wound after necroectomy with subsequent autodermoplasty in all cases contributed to the complete healing of donor sites for 7 days, and the complete engraftment of the skin autotransplant with full recovery of the defect by 12 days after surgery. This preliminary data suggests the potential role of Geprocel in the clinical management of burn treatment.The work is based on the analysis of the treatment results of 35 patients with burn trauma (10 women and 25 men) aged 15 to 55 years who were treated in the burn department of Republican Scientific Centre of Urgent Medical Aid (RSCUMA) between 2017 and 2018. In this study, we report on the use of the hemostatic preparation Geprocel with an autodermoplasty on a wound after necroectomy with subsequent autodermoplasty in all cases contributed to the complete healing of donor sites for 7 days, and the complete engraftment of the skin autotransplant with full recovery of the defect by 12 days after surgery. This preliminary data suggests the potential role of Geprocel in the clinical management of burn treatment

PATIKAweb: A Web interface for analyzing biological pathways through advanced querying and visualization

Summary: PATIKAweb provides a Web interface for retrieving and analyzing biological pathways in the PATIKA database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats. © The Author 2005. Published by Oxford University Press. All rights reserved

PATIKA: An integrated visual environment for collaborative construction and analysis of cellular pathways

Motivation: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. Results: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named PATIKA (Pathway Analysis Tool for Integration and Knowledge Acquisition). PATIKA is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that PATIKA will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development

Algorithms for effective querying of compound graph-based pathway databases

<p>Abstract</p> <p>Background</p> <p>Graph-based pathway ontologies and databases are widely used to represent data about cellular processes. This representation makes it possible to programmatically integrate cellular networks and to investigate them using the well-understood concepts of graph theory in order to predict their structural and dynamic properties. An extension of this graph representation, namely hierarchically structured or compound graphs, in which a member of a biological network may recursively contain a sub-network of a somehow logically similar group of biological objects, provides many additional benefits for analysis of biological pathways, including reduction of complexity by decomposition into distinct components or modules. In this regard, it is essential to effectively query such integrated large compound networks to extract the sub-networks of interest with the help of efficient algorithms and software tools.</p> <p>Results</p> <p>Towards this goal, we developed a querying framework, along with a number of graph-theoretic algorithms from simple neighborhood queries to shortest paths to feedback loops, that is applicable to all sorts of graph-based pathway databases, from PPIs (protein-protein interactions) to metabolic and signaling pathways. The framework is unique in that it can account for compound or nested structures and ubiquitous entities present in the pathway data. In addition, the queries may be related to each other through "AND" and "OR" operators, and can be recursively organized into a tree, in which the result of one query might be a source and/or target for another, to form more complex queries. The algorithms were implemented within the querying component of a new version of the software tool P<smcaps>ATIKA</smcaps><it>web </it>(Pathway Analysis Tool for Integration and Knowledge Acquisition) and have proven useful for answering a number of biologically significant questions for large graph-based pathway databases.</p> <p>Conclusion</p> <p>The P<smcaps>ATIKA</smcaps> Project Web site is <url>http://www.patika.org</url>. P<smcaps>ATIKA</smcaps><it>web </it>version 2.1 is available at <url>http://web.patika.org</url>.</p