1,720,963 research outputs found
Impact of recent protein structure prediction methods on homology, evolutionary and functional inference
Full text linkRecent advances in deep learning techniques have revolutionised protein structure modelling. Since AlphaFold2’s release, a set of tools have now become available to predict native-like structures at near-experimental accuracy for a large fraction of the proteome. This massive amount of structural data is now powering every kind of biological inference requiring structural information. The work presented here features an exploration of the impact of experimental and predicted protein structural information onto homology, evolutionary and functional inference. The first part addresses the issue of accurate multiple sequence alignment (MSA) computation through a novel large-scale algorithmic approach and the systematic use of predicted structural information. In the second part, I explored the contribution of MSAs and structural information to refine phylogenetic and functional inference. On top of developing generic structure-based phylogeny reconstruction methods, I used RBM10, a well characterised splicing factor, as a showcase for the use of predicted structural information to support the inference of functional and phenotypic predictions, especially in the case of pathogenic mutations. The last part of this thesis presents a best-practice bioinformatics pipeline, nf-core/proteinfold, implemented using the Nextflow workflow management system and following nf-core guidelines. This pipeline was developed as a support for the rest of the projects in order to provide a solution to the need of high throughput structure predictions.Els avenços recents en tècniques de deep learning han revolucionat la modelització d'estructures de proteïnes. Desde el llançament d'AlphaFold2, hi ha disponibles un conjunt d'eines per preveure les estructures de forma nativa amb una precisió gairebé experimental per una gran part del proteoma. A dia d'avui, aquesta gran quantitat de data estructural està alimentant tot tipus de inferència biològica que requereix informació estructural. El treball que es presenta aquí conté una exploració de l'impacte de la informació estructural experimental i predictiva de la proteïna en la inferència de la homologia, l'evolució i la funció. La primera part resolt el problema de la computació precisa d'alineacions de seqüències múltiples (MSA) a través d'un nou enfocament algorítmic de gran escala i l'ús sistemàtic de informació estructural predictiva. En la segona part, exploro la contribució de MSAs i la informació estructural per refinar la inferència filogenètica i funcional. A més a més de desenvolupar mètodes genèrics de reconstrucció filogenètica basada en estructures, he utilitzat RBM10, un factor d'empalmament ben caracteritzat, com un exemple per l'ús d'informació estructural predictiva per recolzar la inferència de prediccions funcional i fenotípica, especialment en el cas de mutacions patogèniques. La última part d'aquesta tesis presenta un pipeline bioinformatic best-practise, nf-core/proteinfold, implementat utilitzant el sistema de gestió de fluxos de treball Nextflow i seguint les directrius de nf-core. Aquest pipeline ha sigut desenvolupat com un suport a la resta de projectes i per proveir una solució a la necessitat de prediccions estructurals de gran escala.Programa de doctorat en Biomedicin
Impact of recent protein structure prediction methods on homology, evolutionary and functional inference
No full textRecent advances in deep learning techniques have revolutionised protein structure modelling. Since AlphaFold2’s release, a set of tools have now become available to predict native-like structures at near-experimental accuracy for a large fraction of the proteome. This massive amount of structural data is now powering every kind of biological inference requiring structural information. The work presented here features an exploration of the impact of experimental and predicted protein structural information onto homology, evolutionary and functional inference. The first part addresses the issue of accurate multiple sequence alignment (MSA) computation through a novel large-scale algorithmic approach and the systematic use of predicted structural information. In the second part, I explored the contribution of MSAs and structural information to refine phylogenetic and functional inference. On top of developing generic structure-based phylogeny reconstruction methods, I used RBM10, a well characterised splicing factor, as a showcase for the use of predicted structural information to support the inference of functional and phenotypic predictions, especially in the case of pathogenic mutations. The last part of this thesis presents a best-practice bioinformatics pipeline, nf-core/proteinfold, implemented using the Nextflow workflow management system and following nf-core guidelines. This pipeline was developed as a support for the rest of the projects in order to provide a solution to the need of high throughput structure predictions.Els avenços recents en tècniques de deep learning han revolucionat la modelització d'estructures de proteïnes. Desde el llançament d'AlphaFold2, hi ha disponibles un conjunt d'eines per preveure les estructures de forma nativa amb una precisió gairebé experimental per una gran part del proteoma. A dia d'avui, aquesta gran quantitat de data estructural està alimentant tot tipus de inferència biològica que requereix informació estructural. El treball que es presenta aquí conté una exploració de l'impacte de la informació estructural experimental i predictiva de la proteïna en la inferència de la homologia, l'evolució i la funció. La primera part resolt el problema de la computació precisa d'alineacions de seqüències múltiples (MSA) a través d'un nou enfocament algorítmic de gran escala i l'ús sistemàtic de informació estructural predictiva. En la segona part, exploro la contribució de MSAs i la informació estructural per refinar la inferència filogenètica i funcional. A més a més de desenvolupar mètodes genèrics de reconstrucció filogenètica basada en estructures, he utilitzat RBM10, un factor d'empalmament ben caracteritzat, com un exemple per l'ús d'informació estructural predictiva per recolzar la inferència de prediccions funcional i fenotípica, especialment en el cas de mutacions patogèniques. La última part d'aquesta tesis presenta un pipeline bioinformatic best-practise, nf-core/proteinfold, implementat utilitzant el sistema de gestió de fluxos de treball Nextflow i seguint les directrius de nf-core. Aquest pipeline ha sigut desenvolupat com un suport a la resta de projectes i per proveir una solució a la necessitat de prediccions estructurals de gran escala.Programa de doctorat en Biomedicin
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Επιρροή των σύγχρονων μεθόδων πρόβλεψης πρωτεϊνικών δομών στον προσδιορισμό ομολογίας, εξελικτικών σχέσεων και βιολογικής λειτουργίας
No full textRecent advances in deep learning techniques have revolutionised protein structure modelling. Since AlphaFold2’s release, a set of tools have now become available to predict native-like structures at near-experimental accuracy for a large fraction of the proteome. This massive amount of structural data is now powering every kind of biological inference requiring structural information. The work presented here features an exploration of the impact of experimental and predicted protein structural information onto homology, evolutionary and functional inference. The first part addresses the issue of accurate multiple sequence alignment (MSA) computation through a novel large-scale algorithmic approach and the systematic use of predicted structural information. In the second part, I explored the contribution of MSAs and structural information to refine phylogenetic and functional inference. On top of developing generic structure-based phylogeny reconstruction methods, I used RBM10, a well characterised splicing factor, as a showcase for the use of predicted structural information to support the inference of functional and phenotypic predictions, especially in the case of pathogenic mutations. The last part of this thesis presents a best-practice bioinformatics pipeline, nf-core/proteinfold, implemented using the Nextflow workflow management system and following nf-core guidelines. This pipeline was developed as a support for the rest of the projects in order to provide a solution to the need of high throughput structure predictions.Οι πρόσφατες εξελίξεις στις τεχνικές deep learning έχουν φέρει επανάσταση στη μοντελοποίηση της δομής των πρωτεϊνών. Αρχής γενομένης από την κυκλοφορία του AlphaFold2, έχει πλέον γίνει διαθέσιμο ένα σύνολο εργαλείων για την πρόβλεψη δομών που μοιάζουν με εγγενείς με σχεδόν πειραματική ακρίβεια για ένα μεγάλο μέρος του πρωτεώματος. Αυτή η τεράστια ποσότητα δομικών δεδομένων τροφοδοτεί τώρα κάθε είδους βιολογικό προσδιορισμό που απαιτεί δομικές πληροφορίες. Η εργασία που παρουσιάζεται εδώ περιλαμβάνει μια εξερεύνηση του αντίκτυπου των πειραματικών και προβλεπόμενων δομικών πληροφοριών πρωτεΐνης στην ομολογία, την εξελικτική και λειτουργική εξαγωγή συμπερασμάτων. Το πρώτο μέρος πραγματεύεται το ζήτημα του ακριβούς υπολογισμού της ευθυγράμμισης πολλαπλών αλληλουχιών (MSA) μέσω μιας νέας αλγοριθμικής προσέγγισης μεγάλης κλίμακας και της συστηματικής χρήσης προβλεπόμενων δομικών πληροφοριών. Στο δεύτερο μέρος, διερεύνησα τη συμβολή των MSA και των δομικών πληροφοριών για τη βελτίωση του φυλογενετικού και λειτουργικού προσδιορισμού. Εκτός από την ανάπτυξη γενικών μεθόδων αναδόμησης φυλογένεσης με βάση την πρωτεϊνική δομή, χρησιμοποίησα την πρωτεΐνη RBM10, έναν καλά χαρακτηρισμένο παράγοντα ματίσματος, ως ένα ενδεικτικό παράδειγμα για τη χρησιμότητα των δομικών πληροφοριών προερχόμενων από μοντελοποίηση για την υποστήριξη της εξαγωγής λειτουργικών και φαινοτυπικών προβλέψεων, ειδικά στην περίπτωση παθογόνων μεταλλάξεων. Το τελευταίο μέρος αυτής της διατριβής παρουσιάζει ένα πρόγραμμα βιοπληροφορικής βέλτιστων πρακτικών, nf-core/proteinfold, που υλοποιείται χρησιμοποιώντας το σύστημα διαχείρισης ροής εργασιών Nextflow και ακολουθώντας τις οδηγίες nf-core. Αυτό το πρόγραμμα αναπτύχθηκε ως υποστήριξη για τα υπόλοιπα έργα αυτής της διατριβής προκειμένου να δώσει λύση στην ανάγκη πρόβλεψης πρωτεϊνικών δομών υψηλής απόδοσης
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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