The efficacy potential of cyber security advice as presented in news articles

Cyber security advice is a broad church: it is thematically expansive, comprising expert texts, user-generated data consumed by individual users via informal learning, and much in-between. While there is evidence that cyber security news articles play a role in disseminating cyber security advice, the nature and extent of that role are not clear. We present a corpus of cyber security advice generated from mainstream news articles. The work was driven by two research objectives. The first objective was to ascertain what kind of actionable advice is being disseminated; the second was to explore ways of determining the efficacy potential of news-mediated security advice. The results show an increase in the generation of cyber security news articles, together with increases in vocabulary complexity and reading difficulty. We argue that these could present challenges for vulnerable users. We believe that this corpus and the accompanying analysis have the potential to inform future efforts to quantify and improve the efficacy potential of security advice dissemination

Discovery and interpretation of genetic variation with next‐generation sequencing technologies

Thesis advisor: Gabor T. MarthImprovements in molecular and computational technologies have driven and will continue to drive advances in our understanding of genetic variation and its relationship to phenotypic diversity. Over the last three years, several new DNA sequencing technologies have been developed that greatly improve upon the cost and throughput of the capillary DNA sequencing technologies that were used to sequence the first human genome. The economy of these so‐called “next‐generation” technologies has enabled researchers to conduct genome‐wide studies in genetic variation that were previously intractable or too expensive. However, because the new technologies employ novel molecular techniques, the resulting sequence data is quite different from the capillary sequences to which the genomics field is accustomed. Moreover, the vast amounts of sequence data that these technologies produce present novel statistical and computational challenges in order to make even the simplest observations. The focus of my dissertation has been the development of novel computational and analytical methods that facilitate genome‐wide studies in genetic variation with traditional capillary sequencers and with new sequencing technologies. I present a novel method that produces more accurate error estimates for sequence data from one of these next‐generation sequencing technologies. I also present two studies that illustrate the utility of two such technologies for genome‐wide polymorphism discovery studies in Drosophila melanogaster and Caenorhabditis elegans. These studies accurately estimate the degree of genetic diversity in the fruitfly and nematode, respectively. I later describe how new sequencing approaches can be used to accelerate the mapping of causal genetic mutations in forward geetic screens. Lastly, I remark on where I believe these technologies will lead future studies in human genetic variation and describe their relevance to several of my future research interests.Thesis (PhD) — Boston College, 2008.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Biology

Pybedtools: a flexible Python library for manipulating genomic datasets and annotations

Summary: pybedtools is a flexible Python software library for manipulating and exploring genomic datasets in many common formats. It provides an intuitive Python interface that extends upon the popular BEDTools genome arithmetic tools. The library is well documented and efficient, and allows researchers to quickly develop simple, yet powerful scripts that enable complex genomic analyses

GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations

Modern DNA sequencing technologies enable geneticists to rapidly identify genetic variation among many human genomes. However, isolating the minority of variants underlying disease remains an important, yet formidable challenge for medical genetics. We have developed GEMINI (GEnome MINIng), a flexible software package for exploring all forms of human genetic variation. Unlike existing tools, GEMINI integrates genetic variation with a diverse and adaptable set of genome annotations (e.g., dbSNP, ENCODE, UCSC, ClinVar, KEGG) into a unified database to facilitate interpretation and data exploration. Whereas other methods provide an inflexible set of variant filters or prioritization methods, GEMINI allows researchers to compose complex queries based on sample genotypes, inheritance patterns, and both pre-installed and custom genome annotations. GEMINI also provides methods for ad hoc queries and data exploration, a simple programming interface for custom analyses that leverage the underlying database, and both command line and graphical tools for common analyses. We demonstrate GEMINI's utility for exploring variation in personal genomes and family based genetic studies, and illustrate its ability to scale to studies involving thousands of human samples. GEMINI is designed for reproducibility and flexibility and our goal is to provide researchers with a standard framework for medical genomics

A reference bacterial genome dataset generated on the MinION™ portable single-molecule nanopore sequencer

BACKGROUND: The MinION™ is a new, portable single-molecule sequencer developed by Oxford Nanopore Technologies. It measures four inches in length and is powered from the USB 3.0 port of a laptop computer. The MinION™ measures the change in current resulting from DNA strands interacting with a charged protein nanopore. These measurements can then be used to deduce the underlying nucleotide sequence. FINDINGS: We present a read dataset from whole-genome shotgun sequencing of the model organism Escherichia coli K-12 substr. MG1655 generated on a MinION™ device during the early-access MinION™ Access Program (MAP). Sequencing runs of the MinION™ are presented, one generated using R7 chemistry (released in July 2014) and one using R7.3 (released in September 2014). CONCLUSIONS: Base-called sequence data are provided to demonstrate the nature of data produced by the MinION™ platform and to encourage the development of customised methods for alignment, consensus and variant calling, de novo assembly and scaffolding. FAST5 files containing event data within the HDF5 container format are provided to assist with the development of improved base-calling methods

Can HbA1c detect undiagnosed diabetes in acute medical hospital admissions?

Objective: to study hyperglycaemia in acute medical admissions to Irish regional hospital.Research design and methods: from 2005 to 2007, 2061 white Caucasians, aged &gt;18 years, were admitted by 1/7 physicians. Those with diabetes symptoms/complications but no previous record of hyperglycaemia (n = 390), underwent OGTT with concurrent HbA1c in representative subgroup (n = 148). Comparable data were obtained for 108 primary care patients at risk of diabetes.Results: diabetes was diagnosed immediately by routine practice in 1% (22/2061) [aged 36 (26–61) years (median IQ range)/55% (12/22) male] with pre-existing diabetes/dysglycaemia present in 19% (390/2061) [69 (58–80) years/60% (235/390) male].Possible diabetes symptoms/complications were identified in 19% [70 (59–79) years/57% (223/390) male] with their HbA1c similar to primary care patients [54 (46–61) years], 5.7 (5.3–6.0)%/39 (34–42) mmol/mol (n = 148) vs 5.7 (5.4–6.1)%/39 (36–43) mmol/mol, p = 0.35, but lower than those diagnosed on admission, 10.2 (7.4–13.3)%/88 (57–122) mmol/mol, p &lt; 0.001. Their fasting plasma glucose (FPG) was similar to primary care patients, 5.2 (4.8–5.7) vs 5.2 (4.8–5.9) mmol/L, p = 0.65, but 2hPG higher, 9.0 (7.3–11.4) vs 5.5 (4.4–7.5), p &lt; 0.001.HbA1c identified diabetes in 10% (15/148) with 14 confirmed on OGTT but overall 32% (48/148) were in diabetic range on OGTT. The specificity of HbA1c in 2061 admissions was similar to primary care, 99% vs 96%, p = 0.20, but sensitivity lower, 38% vs 93%, p &lt; 0.001 (63% on FPG/23% on 2hPG, p = 0.037, in those with possible symptoms/complications).Conclusion: HbA1c can play a diagnostic role in acute medicine as it diagnosed another 2% of admissions with diabetes but the discrepancy in sensitivity shows that it does not reflect transient/acute hyperglycaemia resulting from the acute medical event.</p

Implementación de un prototipo funcional de aprendizaje de máquina para identificar correos electrónicos de Spear Phishing

Trabajo de investigaciónEste trabajo tiene como propósito la detección de correos electrónicos Spear Phishing a mediante un prototipo web, debido a que las técnicas de ingeniería social son muy usadas hoy en día para robar a los usuarios datos de identidad personal y/o credenciales de sus cuentas financieras, por esta razón, todas las personas deben implementar una medida para detectar estos ataques de ingeniería social.2 JUSTIFICACIÓN 3 PLANTEAMIENTO DEL PROBLEMA 4 OBJETIVOS 5 MARCOS DE REFERENCIA 6 ESTADO DEL ARTE 7 METODOLOGÍA 8 DESARROLLO DE LA PROPUESTA 9 INSTALACIÓN Y EQUIPO REQUERIDO 10 RESULTADOS 11 CONCLUSIONES 12 TRABAJOS FUTUROS 13 BIBLIOGRAFÍA 14 ANEXOSPregradoIngeniero de Sistema

Combating subclonal evolution of resistant cancer phenotypes

Metastatic breast cancer remains challenging to treat, and most patients ultimately progress on therapy. This acquired drug resistance is largely due to drug-refractory sub-populations (subclones) within heterogeneous tumors. Here, we track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment, including enhanced mesenchymal and growth factor signaling, which may promote drug resistance, and decreased antigen presentation and TNF-α signaling, which may enable immune system avoidance. Some of these phenotypes pre-exist in pre-treatment subclones that become dominant after chemotherapy, indicating selection for resistance phenotypes. Post-chemotherapy cancer cells are effectively treated with drugs targeting acquired phenotypes. These findings highlight cancer's ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves