20 research outputs found
Translational Informatics in Toxicology
No full textThis thesis, and the subjects presented herein, is a condensed representation of most of the comprehensive scientific projects I have been working on, or been involved in, during my years as a PhD student. The work was mainly carried out at the Techical University of Denmark (DTU) (Danish: Danmarks Tekniske Universitet (DTU)), 2011–2017, under the main supervision of Associate Professor Olivier Taboureau and later by Professor Ole Lund. The project has also been supervised by Professor Søren Brunak and Assistant Professor Karine Audouze.Entitled ‘Translational Informatics in Toxicology’, the focus of the project–and the subjects covered within this thesis–is primarily on my work on translational informatics, including, but not limited to, data base management, data integration, data analysis, statistics and web services, in relation to toxicology. The work was mainly conducted as a member of the research group Computational Chemical Biology (CCB), at the Department of Bio and Health Informatics (DBHI) (Danish: Institut for Bio- og Sundhedshedsinformatik (IBSI)), at DTU in Kongens Lyngby, Denmark. Additionally, some parts of the work was carried out during my external stay, visiting our partners in the research group CCB led by John Overrington at the European Bioinformatics Institute (EMBL-EBI), the bioinformatics node of the European Molecular Biology Laboratory (EMBL), located at the Wellcome Genome Campus in Hinxton in Cambridgeshire, the United Kingdom.As a significant amount of time and work, was also put into another project–a small part of the thesis will deal with this work. The project focused on facial appearance, and a great part of this work was conducted by colleagues of mine, where I assisted as a guest member in their research group–Behavial Phenomics–led by Hanne Jarmer, at the DBHI.The PhD was funded by the Innovative Medicines Initiative Joint Undertaking (IMI-JU), as a part of the eTOX project, and by DTU’s PhD scholarship
HExpoChem: a systems biology resource to explore human exposure to chemicals
No full textSummary: Humans are exposed to diverse hazardous chemicals daily. Although an exposure to these chemicals is suspected to have adverse effects on human health, mechanistic insights into how they interact with the human body are still limited. Therefore, acquisition of curated data and development of computational biology approaches are needed to assess the health risks of chemical exposure. Here we present HExpoChem, a tool based on environmental chemicals and their bioactivities on human proteins with the objective of aiding the qualitative exploration of human exposure to chemicals. The chemical–protein interactions have been enriched with a quality-scored human protein–protein interaction network, a protein–protein association network and a chemical–chemical interaction network, thus allowing the study of environmental chemicals through formation of protein complexes and phenotypic outcomes enrichment. Availability: HExpoChem is available at http://www.cbs.dtu.dk/services/HExpoChem-1.0/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online
Eco - sensitive architecture: an examination of the perceptions of different generations of architects
No full textThe ancient people understood the value of the relationship between man and the
environment and that co-existence was therefore protected for the long well being of the mankind. This interdependence increased with the time and architecture acted as a major contributor on modifying the environment. With the passage of time due to various man-made circumstances, this vernacular architectural co-existence began to decrease causing serious environmental disasters, which subjected to numerous deadly diseases. Accordingly, the
society became more conscious about the environmental sustainability and ecology, which added another dimension to architecture as Eco-Sensitivity and new theories and concepts evolved on that. When dealing with these issues by the Sri Lanaku contemporary architectural generations, it was the four pioneer architects. Andrew Boyed, Minette de Silva, Ulrik Plesner and Geoffrey Bawa, who initiated giving priority to the environment. Their concept on adapting vernacular ideas to the contemporary architectural practice, descended from
generation to generation making it an essential thing to study. With this frame work the study aimed at examining the extent of traditional Eco-sensitivc principles and modem environmental movements manifested in the Sri Lankan architectural practice through generations and oven in the future Initially, vernacular architecture was discussed to understand the contribution of it to the betterment of the environment, at the end deriving common principles. This was followed by the evolutionary process of it, due to the influences
on certain periods of the history. The attitudes of the architects on Eco- sensitivity were studied through structured interviews on their work, other than photographic studies, field visits and drawings. The findings of the study showed that there is nothing new in these contemporary theories, but just rediscovering the vernacular ideas, which had long being forgotten. When
studying the contribution of eco-sensilivity to the architectural practice among the generations, it was revealed that there was a greater concern to it during the pioneer era. But in the latter generations, due to various issues such as limited plot sizes and new technology, only a limited number of architects showed positive attitude towards eco-sensitive designing, though they had a great talent to achieve it. Even in the student generation, it was not considered as a major point and only few dealt with greater enthusiasm. On the basis of these findings the author justifies that, this study will help the present as well as the future generations, to alter their attitude on Eco- sensitivity for the betterment of the environment. Finally the study
suggests that, architects should knowledgeable on the applicability of eco-sensitivity in the building process with the new innovations and the way to use it as a design guideline to create architecture which serves to the environment to the bes
Interpretation of appearance: the effect of facial features on first impressions and personality.
No full textAppearance is known to influence social interactions, which in turn could potentially influence personality development. In this study we focus on discovering the relationship between self-reported personality traits, first impressions and facial characteristics. The results reveal that several personality traits can be read above chance from a face, and that facial features influence first impressions. Despite the former, our prediction model fails to reliably infer personality traits from either facial features or first impressions. First impressions, however, could be inferred more reliably from facial features. We have generated artificial, extreme faces visualising the characteristics having an effect on first impressions for several traits. Conclusively, we find a relationship between first impressions, some personality traits and facial features and consolidate that people on average assess a given face in a highly similar manner
The chemical interactome space between the human host and the genetically defined gut metabotypes
No full textThe bacteria that colonize the gastrointestinal tracts of mammals represent a highly selected microbiome that has a profound influence on human physiology by shaping the host’s metabolic and immune system activity. Despite the recent advances on the biological principles that underlie microbial symbiosis in the gut of mammals, mechanistic understanding of the contributions of the gut microbiome and how variations in the metabotypes are linked to the host health are obscure.Here, we mapped the entire metabolic potential of the gut microiome based solely on metagenomics sequencing data derived from fecal samples of 124 Europeans (healthy, obese and with inflammatory bowel disease). Interestingly, three distinct clusters of individuals with high, medium and low metabolic potential were observed. By illustrating these results in the context of bacterial population, we concluded that the abundance of the Prevotella genera is a key factor indicating alow metabolic potential. These metagenome-based metabolic signatures were used to study the interaction networks between bacteria-specific metabolites and human proteins. We found that thirty-three such metabolites interact with disease-relevant protein complexes several of which are highly expressed in cells and tissues involved in the signaling and shaping of the adaptive immune system and associated with squamous cell carcinoma and bladder cancer. From this set ofmetabolites, eighteen are present in DrugBank providing evidence that we carry a natural pharmacy in our guts. Furthermore, we established connections between the systemic effects of non-antibiotic drugs and the gut microbiome of relevance to drug side effects and health-care solutions
Author Correction:Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models
No full textIn the version of this article initially published, Cristina Leal Rodríguez (Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark) was omitted from the author list. The error has been corrected in the HTML and PDF versions of the article</p
Network graph of all significant correlations between <i>Ratings</i>.
No full text<p>The network depicts the relationship between the individual <i>Ratings</i> as the correlation coefficient, r, between scores. A dashed line depicts negative and a solid line positive correlations and the thickness of the line indicates the strength of the relationship with r as the edge label. Relationships significant for both genders are black, for men blue and for women magenta. Three clusters can be seen in the network with <i>Trustworthy, Responsible, Friendly</i> and <i>Intelligent</i> in the first, <i>Extraverted</i>, <i>Adventurous, Emotionally Stable, Attractive</i> and <i>Physically Healthy</i> in the second and <i>Temperamental, Dominating and Masculine</i> in the third. We named the clusters trustworthiness-friendliness, attractiveness-health-extraversion and dominance-masculinity.</p
Prediction of <i>Ratings</i> from facial features.
No full text<p>The plot shows the average correlation coefficient and standard deviation between observed and predicted scores for each <i>Rating</i> and each gender. A linear regression model was built in a 20-fold cross-validation with a varying number of the most correlated facial components as predictors, chosen based on the training set. Standard deviations are gathered by running the calculations thirty times with different folds for each run. The Ratings are in the plot ordered based on performance for the male faces. The size of the points indicates the Cronbach's α for that trait and it is seen that larger α-values correlate positively with prediction performance. Abbreviations for the <i>Ratings</i> are: Trustw. = Trustworthy, Adv. = Adventurous, Temp. = Temperamental, Healthy = Physically Healthy, Ext. = Extraverted, Dom. = Dominating, Att. = Attractive, Masc. = Masculine, Em. Stab. = Emotionally Stable, Resp. = Responsible and Int. = Intelligent.</p
Extreme faces for the <i>Ratings</i>.
No full text<p>For each face pair the left extreme face is predicted as being judged very low for a given trait and the right face as very high. Each face is based on the β-coefficients from the best linear regression model for that given Rating and gender. We generated the faces by multiplying each β-coefficient to either +4 standard deviations or -4 standard deviations of the matching facial component. A: Male extremes for <i>Adventurous</i>. B: Male extremes for <i>Friendly</i>. C: Male extremes for <i>Dominating</i>. D: Female extremes for <i>Adventurous</i>. E) Female extremes for <i>Trustworthy</i>. F: Female extremes for <i>Dominating</i>.</p
Validation of extreme faces.
No full text<p>In the validation we presented four faces to 116 persons and asked them to choose which one they found to represent a given trait the most. The left plot shows results for the male extremes and the right results for the female extremes. The length of each section in each bar indicates the percentage of times the given face was chosen. The dotted line indicates the percentage representing a random selection of the extreme face. In all cases except one the extreme face was chosen more often than random. For the male faces we found the extremes to be chosen significantly over random. For the female faces this was only found for the <i>Friendly</i> and <i>Adventurous</i> extremes. The colours are from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107721#pone.0107721-Brewer1" target="_blank">[33]</a>.</p
