Knowledge transfer processes within “Child rights, classroom and school management”. Factors affecting the knowledge transfer processes on an individual- group- and organizational level

This study aims to answer two research questions with focus in Sida’s International Training Program: Child rights, classroom and school management, the two questions regard the knowledge transfer process. The first one focuses on how the participants of the program express knowledge and knowledge transfer and the second one highlights what contextual factors that affect the processes on three different levels: individual- group- and organizational. These questions are answered through a social constructivistic approach with an adductive perspective which is manifested in qualitative methods as observations of the course made in Sweden and Zambia, observation of former participants accomplished in Uganda and interviews with the mentors conducted in Sweden and other participants done in Uganda. Selected theories presented in the theoretical framework show a diversity of researchers’ regarding their different definitions of knowledge and knowledge transfer, tacit and explicit knowledge and factors affecting the knowledge transfer process. The later theories are structured within individual-, group- and organizational level to follow my second research question. The analysis chapter contains a mixture of theory and results from the observations and interviews. Here the answers to the specific research questions are answered. Definitions of participants’ explanation of knowledge and knowledge transfer are presented and attached together with tacit and explicit knowledge. Factors affecting the knowledge transfer process are presented and evaluated upon. On individual level factors affecting the knowledge transfer process are: how the receiver adapts the knowledge sent, the way it is contextualized to be sent by the sender and to be adjusted to fit the context by the receiver, how the sender is willing to transfer their knowledge, how the sender is willing to share or not and the receivers participation in the process. On group level the main factor affecting the knowledge transfer process are the group dynamics with focus on the relationship between the sender and the receiver. On organizational level there were three major factors that were highlighted: how the organizational environment should be to encourage knowledge transfer, what the organizational culture should feel like to make the participants encouraged to share their knowledge and the communication between the sender and receiver that affects if there will be a transfer or not. Within the discussion chapter, the perspective is widened to include a general discussion about the research questions. Here a discussion about how one perceives knowledge and knowledge transfer is discussed with focus on seeing knowledge as an object or as a process. Further follows a theoretical discussion regarding knowledge as an object or as a process and how it is interlaced with knowledge transfer and knowledge sharing. Also further research topics within the chosen field are elaborated on

Seeds for effective oligonucleotide design

Background: DNA oligonucleotides are a very useful tool in biology. The best algorithms for designing good DNA oligonucleotides are filtering out unsuitable regions using a seeding approach. Determining the quality of the seeds is crucial for the performance of these algorithms.\ud Results: We present a sound framework for evaluating the quality of seeds for oligonucleotide design. The F-score is used to measure the accuracy of each seed. A number of natural candidates are tested: contiguous (BLAST-like), spaced, transitions-constrained, and multiple spaced seeds. Multiple spaced seeds are the best, with more seeds providing better accuracy. Single spaced and transition seeds are very close whereas, as expected, contiguous seeds come last. Increased accuracy comes at the price of reduced efficiency. An exception is that single spaced and transitions-constrained seeds are both more accurate and more efficient than contiguous ones.\ud Conclusions: Our work confirms another application where multiple spaced seeds perform the best. It will be useful in improving the algorithms for oligonucleotide desig

HMM-FRAME: accurate protein domain classification for metagenomic sequences containing frameshift errors

<p>Abstract</p> <p>Background</p> <p>Protein domain classification is an important step in metagenomic annotation. The state-of-the-art method for protein domain classification is profile HMM-based alignment. However, the relatively high rates of insertions and deletions in homopolymer regions of pyrosequencing reads create frameshifts, causing conventional profile HMM alignment tools to generate alignments with marginal scores. This makes error-containing gene fragments unclassifiable with conventional tools. Thus, there is a need for an accurate domain classification tool that can detect and correct sequencing errors.</p> <p>Results</p> <p>We introduce HMM-FRAME, a protein domain classification tool based on an augmented Viterbi algorithm that can incorporate error models from different sequencing platforms. HMM-FRAME corrects sequencing errors and classifies putative gene fragments into domain families. It achieved high error detection sensitivity and specificity in a data set with annotated errors. We applied HMM-FRAME in Targeted Metagenomics and a published metagenomic data set. The results showed that our tool can correct frameshifts in error-containing sequences, generate much longer alignments with significantly smaller E-values, and classify more sequences into their native families.</p> <p>Conclusions</p> <p>HMM-FRAME provides a complementary protein domain classification tool to conventional profile HMM-based methods for data sets containing frameshifts. Its current implementation is best used for small-scale metagenomic data sets. The source code of HMM-FRAME can be downloaded at <url>http://www.cse.msu.edu/~zhangy72/hmmframe/</url> and at <url>https://sourceforge.net/projects/hmm-frame/</url>.</p

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics

Background: Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives. Methods: Our tool, “OMIM Explorer” (http://www.omimexplorer.com), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries—in essence, generating a computationally assisted differential diagnosis informed by the individual’s personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes. Results: We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants. Conclusions: Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge

The Human Phenotype Ontology project:linking molecular biology and disease through phenotype data

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online

Meeting the challenges of implementing rapid genomic testing in acute pediatric care

Authors: Stark, Z. Lunke, S. Brett, G. Tan, N. Stapleton, R. Kumble, S. Yeung, A. Phelan, D. Chong, B. Fernandez, M.F. Marum, J.E. Hunter, M. Jarmolowicz, A. Yael Prawer, Y. Riseley, J.R. Regan, M. Elliott, J. Melissa Martyn, M. Best, S. Tan, T. Clara L Gaff, C.L. and White, S.M

RD-Connect, NeurOmics and EURenOmics: collaborative European initiative for rare diseases

Functional Genomics of Muscle, Nerve and Brain Disorder