AHRD: Automatically Annotate Proteins with Human Readable Descriptions and Gene Ontology Terms

In the postgenomic era it is impossible to annotate the majority of new proteins in any other way than with computational methods. Our tool AHRD automatically annotates proteins with human readable descriptions and Gene Ontology (GO) terms on a genomic scale. It does so by performing a lexical analysis modeled on the decision process of a human curator investigating the protein descriptions of homologous proteins found by sequence similarity. The central questions of this thesis are how GO annotations can be accurately evaluated and how the annotation performance of AHRD can be increased. To this end we firstly generated an unbiased ground truth set of high quality protein annotations with minimal redundancy. It contains many proteins that are difficult to annotate and thus facilitates contrasting annotation methods. Secondly, we implemented and tested three evaluation metrics for the congruence of GO term annotations. The third metric, which employs the structure of the Gene Ontology and the commonness of GO terms to determine the semantic similarity of GO annotations, is able to perform the most nuanced and consistent evaluation. In addition to a preexisting simulated annealing-based approach a genetic algorithm-based machine learning method was implemented to use the aforementioned evaluation metrics to optimize AHRD's input parameters. Although the genetic algorithm was only able to provide small improvements, they were statistically significant and parameter optimization proved to be necessary to achieve optimal annotation performance. In the style of the lexical analysis of candidate descriptions a new GO term-based analysis for candidate annotations was created. This was able to improve AHRD's GO annotation performance and also enabled the incorporation of new quality indicators such as GO term information content and annotation evidence codes which improved the performance further. It also facilitated the annotation with newly combined sets of GO terms instead of only fixed sets obtained from reference proteins. However, this approach proved to be not viable as it resulted in a significant regression of annotation performance. Using our evaluation method we were able to show that AHRD is able to predict description and GO annotations better and at a greater coverage than most of its competitors. Despite the fact that AHRD is tailored for the application to whole proteomes from all branches of life and for ease of use, in the CAFA3 challenge, a community-driven evaluation of GO annotation methods that often do not have these benefits, AHRD was able to show satisfactory results in most categories. In conclusion, we demonstrated a reliable GO annotation evaluation method and used it to develop AHRD's GO annotation from an afterthought to a mature feature. We showed that AHRD is not only successful at the annotation of descriptions but also at GO terms, while staying applicable in whole genome projects

International Student Mobility: An Identity Development Task?

Based on the review of literature on internationalization of education and on identity formation pro cesses in young adults, this cross - sectional study aims to investigate to which extent self - perceived dimensions of identity are associated to the main moti vations to study abroad. The participants in this study were 429 international university students of different nationalities. Findings revealed that the motivation to study abroa d for personal growth is strongly associated to the commitment and in - depth e xploration identity processes, whereas the motivation to study abroad with the aim of changing life style and enlarging job opportunities is positively associated with reconsideration of commitment and in - depth exploration. Furthermore, identity achieved s tudents showed the highest motivation to s tudy abroad for personal growth, while the motivation to study abroad to positively change life - styles and work conditions is strongly associated with the positive facet of identity crisis, which is otherwise calle d searching - moratorium status. Based on these results, the present survey provides useful questions and hypothesis for future researc

Amyloid and SCD jointly predict cognitive decline across Chinese and German cohorts.

INTRODUCTION Subjective cognitive decline (SCD) in amyloid-positive (Aβ+) individuals was proposed as a clinical indicator of Stage 2 in the Alzheimer's disease (AD) continuum, but this requires further validation across cultures, measures, and recruitment strategies. METHODS Eight hundred twenty-one participants from SILCODE and DELCODE cohorts, including normal controls (NC) and individuals with SCD recruited from the community or from memory clinics, underwent neuropsychological assessments over up to 6 years. Amyloid positivity was derived from positron emission tomography or plasma biomarkers. Global cognitive change was analyzed using linear mixed-effects models. RESULTS In the combined and stratified cohorts, Aβ+ participants with SCD showed steeper cognitive decline or diminished practice effects compared with NC or Aβ- participants with SCD. These findings were confirmed using different operationalizations of SCD and amyloid positivity, and across different SCD recruitment settings. DISCUSSION Aβ+ individuals with SCD in German and Chinese populations showed greater global cognitive decline and could be targeted for interventional trials. HIGHLIGHTS SCD in amyloid-positive (Aβ+) participants predicts a steeper cognitive decline. This finding does not rely on specific SCD or amyloid operationalization. This finding is not specific to SCD patients recruited from memory clinics. This finding is valid in both German and Chinese populations. Aβ+ older adults with SCD could be a target population for interventional trials

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

Addressing climate change with behavioral science:A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p

Addressing climate change with behavioral science: A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

Addressing climate change with behavioral science:A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.</p