FunSimMat update: new features for exploring functional similarity

Quantifying the functional similarity of genes and their products based on Gene Ontology annotation is an important tool for diverse applications like the analysis of gene expression data, the prediction and validation of protein functions and interactions, and the prioritization of disease genes. The Functional Similarity Matrix (FunSimMat, http://www.funsimmat.de) is a comprehensive database providing various precomputed functional similarity values for proteins in UniProtKB and for protein families in Pfam and SMART. With this update, we significantly increase the coverage of FunSimMat by adding data from the Gene Ontology Annotation project as well as new functional similarity measures. The applicability of the database is greatly extended by the implementation of a new Gene Ontology-based method for disease gene prioritization. Two new visualization tools allow an interactive analysis of the functional relationships between proteins or protein families. This is enhanced further by the introduction of an automatically derived hierarchy of annotation classes. Additional changes include a revised user front-end and a new RESTlike interface for improving the user-friendliness and online accessibility of FunSimMat

Combining protein structure prediction with experiments and functional information

Proteins are key players in all cells of living organisms. In particular, knowledge of the spatial protein structure may give fundamental insights into protein function and disease processes. For many years, the successful prediction of the structural and functional properties of proteins has been a major research field in bioinformatics. This field is also addressed in this work, which comprises an applied biomedical and a methodological part. Comprehensive application studies of bioinformatics approaches were performed, which primarily targeted autoinflammatory and neurodegenerative diseases. A variety of computational tools was used to analyze medically relevant proteins and to evaluate experimental data. Many bioinformatics methods were applied to predict the molecular structure and function of proteins. The results provided a rationale for the design, prioritization, and interpretation of experiments performed by cooperation partners. Some of the generated biological hypotheses were tested and confirmed by experiments. In addition, the application studies revealed limitations of current bioinformatics techniques, which led to suggestions for novel approaches. Three new computational methods were developed to support the prediction of the secondary and tertiary structure of proteins and the investigation of their interaction networks. First, consensus formation between three different methods for secondary structure prediction was shown to considerably improve the prediction quality and reliability. Second, in order to utilize experimental measurements in tertiary structure prediction, scoring functions were implemented that incorporate distance constraints into the alignment evaluation, thus increasing the fold recognition rate. Third, an automatic procedure for decomposing protein networks into interacting domains was designed to obtain a more detailed molecular view of protein-protein interactions, facilitating further functional and structural analyses.Proteinen kommt in allen Zellen lebender Organismen eine Schlüsselrolle zu. Insbesondere die Kenntnis der Raumstruktur von Proteinen kann fundamentale Einsichten in ihre Funktion und in Krankheitsprozesse liefern. Seit vielen Jahren ist die erfolgreiche Vorhersage struktureller und funktioneller Eigenschaften von Proteinen ein wichtiges Forschungsgebiet in der Bioinformatik. Dieses Gebiet ist auch Gegenstand der vorliegenden Arbeit, welche einen angewandten biomedizinischen und einen methodischen Teil umfasst. Es wurden umfangreiche Applikationsstudien von bioinformatischen Verfahren durchgeführt, die sich vornehmlich mit autoinflammatorischen und neurodegenerativen Erkrankungen befassten. Verschiedene Computerwerkzeuge wurden verwendet, um medizinisch relevante Proteine zu analysieren und experimentelle Daten auszuwerten. Es kamen viele Bioinformatikmethoden zur Anwendung, um die molekulare Struktur und Funktion von Proteinen vorherzusagen. Die Ergebnisse dienten als Grundlage für die Planung, Priorisierung und Interpretation von Experimenten, die von Kooperationspartnern durchgeführt wurden. Einige der generierten biologischen Hypothesen wurden durch Experimente überprüft und bestätigt. Zusätzlich deckten die Applikationsstudien Grenzen von Bioinformatikmethoden auf, was zu Vorschlägen für neuartige Verfahren führte. So wurden drei neue rechnerbasierte Methoden entwickelt, um die Vorhersage der Sekundär- und Tertiärstruktur von Proteinen sowie die Untersuchung ihrer Interaktionsnetzwerke zu unterstützen. Erstens wurde gezeigt, dass die Bildung eines Konsensus zwischen drei verschiedenen Methoden der Sekundärstrukturvorhersage die Vorhersagequalität und -verlässlichkeit erheblich verbessert. Zweitens wurden zur Nutzung experimenteller Messungen in der Tertiärstrukturvorhersage Bewertungsfunktionen implementiert, die Distanzbeschränkungen in die Alignmentevaluation einbinden, um die Faltungserkennungsrate zu erhöhen. Drittens wurde eine automatische Prozedur zur Dekomposition von Proteinnetzwerken in interagierende Domänen entworfen, um eine detailliertere molekulare Sicht von Interaktionen zwischen Proteinen zu erhalten. Hierdurch werden weitere Analysen zu Funktion und Struktur erleichtert

GOTax: investigating biological processes and biochemical activities along the taxonomic tree

GOTax, a novel web-based platform that integrates protein annotation with protein family classification and taxonomy, allows for an extensive assessment of functional similarity between proteins and for comparing and analyzing the distribution of protein families and protein functions over different taxonomic groups

Integrative visual analysis of protein sequence mutations

BACKGROUND: An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations. To understand the functional impact of amino acid changes, the multiple biological properties of protein residues have to be considered together. RESULTS: Here, we present a novel visual approach for analyzing residue mutations. It combines different biological visualizations and integrates them with molecular data derived from external resources. To show various aspects of the biological information on different scales, our approach includes one-dimensional sequence views, three-dimensional protein structure views and two-dimensional views of residue interaction networks as well as aggregated views. The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them. In particular, the protein mutations are mapped onto the views together with further functional and structural information. We also assess the impact of individual amino acid changes by the detailed analysis and visualization of the involved residue interactions. We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest. CONCLUSIONS: Our visual approach and software greatly facilitate the integrative and interactive analysis of protein mutations based on complementary visualizations. The different data views offered to the user are enriched with information about molecular properties of amino acid residues and further biological knowledge

Applications of semantic similarity measures

There has been much interest in uncovering protein-protein interactions and their underlying domain-domain interactions. Many experimental techniques have been developed, for example yeast-two-hybrid screening and tandem affinity purification. Since it is time consuming and expensive to perform exhaustive experimental screens, in silico methods are used for predicting interactions. However, all experimental and computational methods have considerable false positive and false negative rates. Therefore, it is necessary to validate experimentally determined and predicted interactions. One possibility for the validation of interactions is the comparison of the functions of the proteins or domains. Gene Ontology (GO) is widely accepted as a standard vocabulary for functional terms, and is used for annotating proteins and protein families with biological processes and their molecular functions. This annotation can be used for a functional comparison of interacting proteins or domains using semantic similarity measures. Another application of semantic similarity measures is the prioritization of disease genes. It is know that functionally similar proteins are often involved in the same or similar diseases. Therefore, functional similarity is used for predicting disease associations of proteins. In the first part of my talk, I will introduce some semantic and functional similarity measures that can be used for comparison of GO terms and proteins or protein families. Then, I will show their application for determining a confidence threshold for domain-domain interaction predictions. Additionally, I will present FunSimMat (http://www.funsimmat.de/), a comprehensive resource of functional similarity values available on the web. In the last part, I will introduce the problem of comparing diseases, and a first attempt to apply functional similarity measures based on GO to this problem

Mindfulness-Based Student Training Improves Vascular Variability Associated With Sustained Reductions in Physiological Stress Response

In today's fast-paced society, chronic stress has become an increasing problem, as it can lead to psycho-physiological health problems. University students are also faced with stress due to the demands of many courses and exams. The positive effects of mindfulness-based stress reduction (MBSR) on stress management and self-regulation have already been studied. We have developed a new mindfulness intervention tailored for students—the Mindfulness-Based Student Training (MBST). In this study, we present longitudinal results of the MBST evaluation. Biosignal analysis methods, including pulse wave variability (PWV), heart rate variability, and respiratory activity, were used to assess participants' state of autonomic regulation during the 12-week intervention and at follow-up. The progress of the intervention group (IGR, N = 31) up to 3 months after the end of MBST was compared with that of a control group (CON , N = 34). In addition, the long-term effect for IGR up to 1 year after intervention was examined. The analysis showed significant positive changes in PWV exclusively for IGR. This positive effect, particularly on vascular function, persists 1 year after the end of MBST. These results suggest a physiologically reduced stress level in MBST participants and a beneficial preventive health care program for University students

Electronic properties of curved few-layers graphene: a geometrical approach

We show the presence of non-relativistic L\'evy-Leblond fermions in flat three- and four-layers graphene with AB stacking, extending the results obtained in [Curvatronics2017] for bilayer graphene. When the layer is curved we obtain a set of equations for Galilean fermions that are a variation of those of L\'evy-Leblond with a well defined combination of pseudospin, and that admit L\'evy-Leblond spinors as solutions in an approriate limit. The local energy of such Galilean fermions is sensitive to the intrinsic curvature of the surface. We discuss the relationship between two-dimensional pseudospin, labelling layer degrees of freedom, and the different energy bands. For L\'evy-Leblond fermions an interpretation is given in terms of massless fermions in an effective 4D spacetime, and in this case the pseudospin is related to four dimensional chirality. A non-zero energy band gap between conduction and valence electronic bands is obtained for surfaces with positive curvature.Comment: 16 pages, 4 figures. Matches the published version. Refined theory that describes the unique combination of isospin states ocurring in curved bilayer graphene sheet

Influence of magnetic domain walls on all-optical magnetic toggle switching in a ferrimagnetic GdFe film

We present a microscopic magnetic domain imaging study of single-shot all-optical magnetic toggle switching of a ferrimagnetic Gd(26)Fe(74) film with out-of-plane easy axis of magnetization by X-ray magnetic circular dichroism photoelectron emission microscopy. Individual linearly polarized laser pulses of 800 nm wavelength and 100 fs duration above a certain threshold fluence reverse the sample magnetization, independent of the magnetization direction, the so-called toggle switching. Local deviations from this deterministic behavior close to magnetic domain walls are studied in detail. Reasons for nondeterministic toggle switching are related to extrinsic effects, caused by pulse-to-pulse variations of the exciting laser system, and to intrinsic effects related to the magnetic domain structure of the sample. The latter are, on the one hand, caused by magnetic domain wall elasticity, which leads to a reduction of the domain-wall length at features with sharp tips. These features appear after the optical switching at positions where the line of constant threshold fluence in the Gaussian footprint of the laser pulse comes close to an already existing domain wall. On the other hand, we identify the presence of laser-induced domain-wall motion in the toggle-switching event as a further cause for local deviations from purely deterministic toggle switching

Critical Behavior and Axis Defining Symmetry Breaking in Hydra Embryonic Development

The formation of a hollow cellular sphere is often one of the first steps of multicellular embryonic development. In the case of Hydra, the sphere breaks its initial symmetry to form a foot-head axis. During this process a gene, ks1, is increasingly expressed in localized cell domains whose size distribution becomes scale-free at the axis-locking moment. We show that a physical model based solely on the production and exchange of ks1-promoting factors among neighboring cells robustly reproduces the scaling behavior as well as the experimentally observed spontaneous and temperature-directed symmetry breaking

Incidence and challenges of helicopter emergency medical service (HEMS) rescue missions with helicopter hoist operations: analysis of 11,228 daytime and nighttime missions in Switzerland

Objective: We aimed to investigate the medical characteristics of helicopter hoist operations (HHO) in HEMS missions. Methods: We designed a retrospective study evaluating all HHO and other human external cargo (HEC) missions performed by Swiss Air-Rescue (Rega) between January 1, 2010, and December 31, 2019. Results: During the study period, 9,963 (88.7 %) HEMS missions with HHO and HEC were conducted during the day, and 1,265 (11.3 %) at night. Of the victims with time-critical injuries (NACA ≥ 4), 21.1 % (n = 400) reached the hospital within 60 min during the day, and 9.1 % (n = 18) at night. Nighttime missions, a trauma diagnosis, intubation on-site, and NACA Score ≥ 4 were independently and highly significantly associated with longer mission times (p < 0.001). The greatest proportion of patients who needed hoist or HEC operations in the course of the HEMS mission during the daytime sustained moderate injuries (NACA 3, n = 3,731, 37.5 %) while practicing recreational activities (n = 5,492, 55.1 %). In daytime HHO missions, the most common medical interventions performed were insertion of a peripheral intravenous access (n = 3,857, 38.7 %) and administration of analgesia (n = 3,121, 31.3 %). Conclusions: Nearly 20 % of patients who needed to be evacuated by a hoist were severely injured, and complex and lifesaving medical interventions were necessary before the HHO procedure. Therefore, only adequately trained and experienced medical crew members should accompany HHO missions