FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the FAIRness of NASAs GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility

Semantic Analysis of Email Using Domain Ontologies and WordNet

The problem of capturing and accessing knowledge in paper form has been supplanted by a problem of providing structure to vast amounts of electronic information. Systems that can construct semantic links for natural language documents like email messages automatically will be a crucial element of semantic email tools. We have designed an information extraction process that can leverage the knowledge already contained in an existing semantic web, recognizing references in email to existing nodes in a network of ontology instances by using linguistic knowledge and knowledge of the structure of the semantic web. We developed a heuristic score that uses several forms of evidence to detect references in email to existing nodes in the Semanticorganizer repository's network. While these scores cannot directly support automated probabilistic inference, they can be used to rank nodes by relevance and link those deemed most relevant to email messages

Assessment of Identity Disturbance: Factor Structure and Validation of the Personality Structure Questionnaire in an Italian Sample

here are few brief measures of identity disturbance for use in clinical practice that have been subject to any cross - culturally validation . This study investigated the construct validity of the Personality Structure Questionnaire (PSQ) in Italian clinical (N=237) and community ( N=296) samples . Confirmatory factor analysis was conducted to investigate the internal structure of the PSQ. A three – factor structure (i.e., differing self - states, mood variability and behavioral loss of control) including a second - order factor provided the best fit to the data . This structure was demonstrated to be invariant across sex and clinical diagnosis , with clinical diagnosis significantly predicting increased PSQ scores . A g lobal PSQ score of between 26 - 28 was found to be an appropriate cut-off for assisting in diagnostic processes. Implications for the assessment and treatment of psychological disorders with a marked identity disturbance component are discussed

Influence of Grapevine Leafroll-associated Virus-3 in Mature Plants of Vitis vinifera L. cv Albariño on 110R and 196.17C Rootstocks

The detrimental effects of grapevine leafroll disease (GLD) have been documented mainly in young plantsand little data is available on infected grapevines when they reach maturity. This study examined theinfluence of the rootstock on the effect of GLRaV-3 in a 20-year-old Vitis vinifera cv Albariño vineyard inwhich the virus has been spread by Planococcus ficus. Plants grafted on Richter 110 or Castell 196.17 withsimilar development were analysed for grapevine leafroll-associated viruses. In particular, 25 GLRaV-3-infected and 25 leafroll-free and asymptomatic vines were selected and monitored during a period of threeyears to determine grape yield and must components. Although the virus infection affected plants on bothrootstocks, it caused a greater effect on plants grafted onto 110R, with average accumulated yield losses ofup to 33%, relative to losses of 16% for plants on 196.17C. The sugar content was lower in the must frominfected plants on 110R (-2.1ºBrix) than in the must from plants on 196.17C (-1.5ºBrix). The presence ofthe virus was associated with decreased concentrations of primary amino nitrogen (PAN) and ammonium(NH4+), with the greatest effect for 110R (-35%). As 110R is the most used rootstock in Spain, particularcare must be taken to prevent the transmission of GLRaV-3 to certified virus-free plants on 110R in newvineyards. In sensitive varieties such as Albariño, particularly in areas with an active spread of the virusby mealybugs, grafting on 196.17C seems to minimise the effect that GLD has in a medium to long term

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems

NASA's GeneLab Phase II: Federated Search and Data Discovery

GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics