DNR Interactive Mapping: A tool for Iowa Agriculture, 2006

The planning tools you need to improve both your farming operation and Iowa’s streams and lakes are right at your fingertips. With DNR interactive mapping online, you can access a large amount of information for free and without special software.

Mapping Nursing language terms of Parkinson's disease

OBJECTIVE Implementing cross-mapping of Nursing language terms with the terminology of NANDA International, contained in records of patients with Parkinson's disease in rehabilitation. METHOD Descriptive study of cross mapping, carried out in three steps. A simple random sample of 67 files of patients who participated in the rehabilitation in the period between March 2009 and April 2013. RESULTS We identified 454 terms of Nursing language that resulted in 54 diagnoses after cross-mapping, present in 11 of the 13 taxonomy domains. The most mapped diagnosis was "Impaired urinary elimination" (59.7%), followed by "Urgent urinary incontinence" (55.2%), "Willingness to self-control improved health" (50.7%), "Constipation" (47.8%) and "Compromised physical mobility" (29.9%). Seven described terms were not mapped due to a corresponding defining characteristic being absent. CONCLUSION It was possible to determine the profile of patients, as well as the complexity of nursing care in the rehabilitation of patients with Parkinson's disease.

The InterPro protein families database: the classification resource after 15 years.

The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.

Mapping of the genes coding for the two major vaccinia virus core polypeptides.

We have mapped the genes coding for two major structural polypeptides of the vaccinia virus core by hybrid selection and transcriptional mapping. First, RNA was selected by hybridization to restriction fragments of the vaccinia virus genome, translated in vitro and the products were immunoprecipitated with antibodies against the two polypeptides. This approach allowed us to map the genes to the left hand end of the largest Hind III restriction fragment of 50 kilobase pairs. Second, transcriptional mapping of this region of the genome revealed the presence of the two expected RNAs. Both RNAs are transcribed from the leftward reading strand and the 5'-ends of the genes are separated by about 7.5 kilobase pairs of DNA. Thus, two genes encoding structural polypeptides with a similar location in the vaccinia virus particle are clustered at approximately 105 kilobase pairs from the left hand end of the 180 kilobase pair vaccinia virus genome.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Improving Transition Outcomes: Resource Mapping Workshop: Additional Information

Information used/presented during the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Service Matrix

Resource Mapping tool from the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Resource List

Resource Mapping resources shared during the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Business Survey

Business survey tool from the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Content Outline

Content outline used during the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Activities

Activities used during the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: Announcement

Announcement of the Improving Transition Outcomes Resource Mapping Workshops

Improving Transition Outcomes: Resource Mapping Workshop: General Information

Information shared at the Improving Transition Outcomes Resource Mapping Workshops