Browsing by Subject "ONTOLOGY"

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  • Jiang, Yuxiang; Oron, Tal Ronnen; Clark, Wyatt T.; Bankapur, Asma R.; D'Andrea, Daniel; Lepore, Rosalba; Funk, Christopher S.; Kahanda, Indika; Verspoor, Karin M.; Ben-Hur, Asa; Koo, Da Chen Emily; Penfold-Brown, Duncan; Shasha, Dennis; Youngs, Noah; Bonneau, Richard; Lin, Alexandra; Sahraeian, Sayed M. E.; Martelli, Pier Luigi; Profiti, Giuseppe; Casadio, Rita; Cao, Renzhi; Zhong, Zhaolong; Cheng, Jianlin; Altenhoff, Adrian; Skunca, Nives; Dessimoz, Christophe; Dogan, Tunca; Hakala, Kai; Kaewphan, Suwisa; Mehryary, Farrokh; Salakoski, Tapio; Ginter, Filip; Fang, Hai; Smithers, Ben; Oates, Matt; Gough, Julian; Toronen, Petri; Koskinen, Patrik; Holm, Liisa; Chen, Ching-Tai; Hsu, Wen-Lian; Bryson, Kevin; Cozzetto, Domenico; Minneci, Federico; Jones, David T.; Chapman, Samuel; Dukka, B. K. C.; Khan, Ishita K.; Kihara, Daisuke; Ofer, Dan; Rappoport, Nadav; Stern, Amos; Cibrian-Uhalte, Elena; Denny, Paul; Foulger, Rebecca E.; Hieta, Reija; Legge, Duncan; Lovering, Ruth C.; Magrane, Michele; Melidoni, Anna N.; Mutowo-Meullenet, Prudence; Pichler, Klemens; Shypitsyna, Aleksandra; Li, Biao; Zakeri, Pooya; ElShal, Sarah; Tranchevent, Leon-Charles; Das, Sayoni; Dawson, Natalie L.; Lee, David; Lees, Jonathan G.; Sillitoe, Ian; Bhat, Prajwal; Nepusz, Tamas; Romero, Alfonso E.; Sasidharan, Rajkumar; Yang, Haixuan; Paccanaro, Alberto; Gillis, Jesse; Sedeno-Cortes, Adriana E.; Pavlidis, Paul; Feng, Shou; Cejuela, Juan M.; Goldberg, Tatyana; Hamp, Tobias; Richter, Lothar; Salamov, Asaf; Gabaldon, Toni; Marcet-Houben, Marina; Supek, Fran; Gong, Qingtian; Ning, Wei; Zhou, Yuanpeng; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Toppo, Stefano; Ferrari, Carlo; Giollo, Manuel; Piovesan, Damiano; Tosatto, Silvio C. E.; del Pozo, Angela; Fernandez, Jose M.; Maietta, Paolo; Valencia, Alfonso; Tress, Michael L.; Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Rehman, Hafeez Ur; Re, Matteo; Mesiti, Marco; Valentini, Giorgio; Bargsten, Joachim W.; van Dijk, Aalt D. J.; Gemovic, Branislava; Glisic, Sanja; Perovic, Vladmir; Veljkovic, Veljko; Veljkovic, Nevena; Almeida-e-Silva, Danillo C.; Vencio, Ricardo Z. N.; Sharan, Malvika; Vogel, Joerg; Kansakar, Lakesh; Zhang, Shanshan; Vucetic, Slobodan; Wang, Zheng; Sternberg, Michael J. E.; Wass, Mark N.; Huntley, Rachael P.; Martin, Maria J.; O'Donovan, Claire; Robinson, Peter N.; Moreau, Yves; Tramontano, Anna; Babbitt, Patricia C.; Brenner, Steven E.; Linial, Michal; Orengo, Christine A.; Rost, Burkhard; Greene, Casey S.; Mooney, Sean D.; Friedberg, Iddo; Radivojac, Predrag (2016)
    Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
  • Patwardhan, Ardan; Brandt, Robert; Butcher, Sarah J.; Collinson, Lucy; Gault, David; Grunewald, Kay; Hecksel, Corey; Huiskonen, Juha T.; Iudin, Andrii; Jones, Martin L.; Korir, Paul K.; Koster, Abraham J.; Lagerstedt, Ingvar; Lawson, Catherine L.; Mastronarde, David; McCormick, Matthew; Parkinson, Helen; Rosenthal, Peter B.; Saalfeld, Stephan; Saibil, Helen R.; Sarntivijai, Sirarat; Valero, Irene Solanes; Subramaniam, Sriram; Swedlow, Jason R.; Tudose, Ilinca; Winn, Martyn; Kleywegt, Gerard J. (2017)
    The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.
  • Das Roy, Rishi; Hallikas, Outi; Christensen, Mona M.; Renvoise, Elodie; Jernvall, Jukka (2021)
    Author summary Development of organs is typically associated with small and hard to detect changes in gene expression. Here we examined how often genes regulating specific organs are neighbours to each other in the genome, and whether this gene neighbourhood helps in the detection of changes in gene expression. We found that genes regulating individual organ development are very rarely close to each other in the mouse and human genomes. We built an algorithm, called DELocal, to detect changes in gene expression that incorporates information about neighbouring genes. Using transcriptomes of developing mouse molar teeth containing gene expression profiles of thousands of genes, we show how genes regulating tooth development are ranked high by DELocal even if their expression level changes are subtle. We propose that developmental biology studies can benefit from gene neighbourhood analyses in the detection of differential expression and identification of organ specific genes. Although most genes share their chromosomal neighbourhood with other genes, distribution of genes has not been explored in the context of individual organ development; the common focus of developmental biology studies. Because developmental processes are often associated with initially subtle changes in gene expression, here we explored whether neighbouring genes are informative in the identification of differentially expressed genes. First, we quantified the chromosomal neighbourhood patterns of genes having related functional roles in the mammalian genome. Although the majority of protein coding genes have at least five neighbours within 1 Mb window around each gene, very few of these neighbours regulate development of the same organ. Analyses of transcriptomes of developing mouse molar teeth revealed that whereas expression of genes regulating tooth development changes, their neighbouring genes show no marked changes, irrespective of their level of expression. Finally, we test whether inclusion of gene neighbourhood in the analyses of differential expression could provide additional benefits. For the analyses, we developed an algorithm, called DELocal that identifies differentially expressed genes by comparing their expression changes to changes in adjacent genes in their chromosomal regions. Our results show that DELocal removes detection bias towards large changes in expression, thereby allowing identification of even subtle changes in development. Future studies, including the detection of differential expression, may benefit from, and further characterize the significance of gene-gene neighbour relationships.
  • Fernández-Llamazares Onrubia, Álvaro; Virtanen, Pirjo Kristiina (2020)
    Throughout the Amazon, notions of ownership and mastership shape the use of natural resources among many Indigenous communities. These ideas are reflected in the figure of game masters (i.e. spiritual beings who own the animals), which are widespread among Indigenous peoples across the Amazon Basin. In this paper, we explore the diverse biocultural manifestations of this socio-cosmology, focusing on the game masters' dynamic roles, histories and functions. Our review highlights the breadth and depth of ideas, practices, and rituals used to regulate humans' relations with these non-human agencies. It illustrates how the relations established between Indigenous communities and animals reflect both reciprocity and other asymmetrical types of dependency. This complex and sophisticated socio-cosmology underpins Indigenous understandings of sustainability in the world's largest tropical rainforest.
  • Genetics of DNA Methylation Consortium; BIOS Consortium; van Dongen, Jenny; Lundgren, Sara; Ollikainen, Miina; Kaprio, Jaakko (2021)
    The mechanisms underlying how monozygotic (or identical) twins arise are yet to be determined. Here, the authors investigate this in an epigenome-wide association study, showing that monozygotic twinning has a characteristic DNA methylation signature in adult somatic tissues. Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.
  • Siragusa, Laura; Westman, Clinton; Moritz, Sarah (2020)
    We introduce and elaborate on the notion of "shared breath" as a way of understanding human and nonhuman copresence and offer descriptions and narratives about three Indigenous groups in Russia and Canada, namely, Veps, Western Woods Cree, and Interior Salish St'at'imc. These data illustrate vividly how the underused metaphor of shared breath sheds light on active participation in life by and respectful relations with nonhuman beings, thus surpassing other overly used spatial, physical, and spiritual metaphors. We move beyond the physical aspects of discrete spaces and materials in extending consideration to pertinent metaphorical and tangible aspects of the verbal, sonorous, and ritual performances undertaken by humans in order to negotiate and reinforce relations with other beings. Relationality is continuously accommodated and regenerated by human and nonhuman agencies through ritual acts that include blowing, chants, breathing, drumming, visualizing, and smoking. The shared breath through which these encounters take place emblematizes turning moments, when new directions may be taken and long-term relations of respect may be established, validated, and reinforced. Shared breath is both a medium and a modality of shamanic and animist relationality, offering a new way of looking at human-nonhuman contact and exchange in animist ritual contexts and beyond.
  • Zhou, Naihui; Jiang, Yuxiang; Bergquist, Timothy R.; Lee, Alexandra J.; Kacsoh, Balint Z.; Crocker, Alex W.; Lewis, Kimberley A.; Georghiou, George; Nguyen, Huy N.; Hamid, Md Nafiz; Davis, Larry; Dogan, Tunca; Atalay, Volkan; Rifaioglu, Ahmet S.; Dalkiran, Alperen; Atalay, Rengul Cetin; Zhang, Chengxin; Hurto, Rebecca L.; Freddolino, Peter L.; Zhang, Yang; Bhat, Prajwal; Supek, Fran; Fernandez, Jose M.; Gemovic, Branislava; Perovic, Vladimir R.; Davidovic, Radoslav S.; Sumonja, Neven; Veljkovic, Nevena; Asgari, Ehsaneddin; Mofrad, Mohammad R. K.; Profiti, Giuseppe; Savojardo, Castrense; Martelli, Pier Luigi; Casadio, Rita; Boecker, Florian; Schoof, Heiko; Kahanda, Indika; Thurlby, Natalie; McHardy, Alice C.; Renaux, Alexandre; Saidi, Rabie; Gough, Julian; Freitas, Alex A.; Antczak, Magdalena; Fabris, Fabio; Wass, Mark N.; Hou, Jie; Cheng, Jianlin; Wang, Zheng; Romero, Alfonso E.; Paccanaro, Alberto; Yang, Haixuan; Goldberg, Tatyana; Zhao, Chenguang; Holm, Liisa; Törönen, Petri; Medlar, Alan J.; Zosa, Elaine; Borukhov, Itamar; Novikov, Ilya; Wilkins, Angela; Lichtarge, Olivier; Chi, Po-Han; Tseng, Wei-Cheng; Linial, Michal; Rose, Peter W.; Dessimoz, Christophe; Vidulin, Vedrana; Dzeroski, Saso; Sillitoe, Ian; Das, Sayoni; Lees, Jonathan Gill; Jones, David T.; Wan, Cen; Cozzetto, Domenico; Fa, Rui; Torres, Mateo; Vesztrocy, Alex Warwick; Rodriguez, Jose Manuel; Tress, Michael L.; Frasca, Marco; Notaro, Marco; Grossi, Giuliano; Petrini, Alessandro; Re, Matteo; Valentini, Giorgio; Mesiti, Marco; Roche, Daniel B.; Reeb, Jonas; Ritchie, David W.; Aridhi, Sabeur; Alborzi, Seyed Ziaeddin; Devignes, Marie-Dominique; Koo, Da Chen Emily; Bonneau, Richard; Gligorijevic, Vladimir; Barot, Meet; Fang, Hai; Toppo, Stefano; Lavezzo, Enrico; Falda, Marco; Berselli, Michele; Tosatto, Silvio C. E.; Carraro, Marco; Piovesan, Damiano; Rehman, Hafeez Ur; Mao, Qizhong; Zhang, Shanshan; Vucetic, Slobodan; Black, Gage S.; Jo, Dane; Suh, Erica; Dayton, Jonathan B.; Larsen, Dallas J.; Omdahl, Ashton R.; McGuffin, Liam J.; Brackenridge, Danielle A.; Babbitt, Patricia C.; Yunes, Jeffrey M.; Fontana, Paolo; Zhang, Feng; Zhu, Shanfeng; You, Ronghui; Zhang, Zihan; Dai, Suyang; Yao, Shuwei; Tian, Weidong; Cao, Renzhi; Chandler, Caleb; Amezola, Miguel; Johnson, Devon; Chang, Jia-Ming; Liao, Wen-Hung; Liu, Yi-Wei; Pascarelli, Stefano; Frank, Yotam; Hoehndorf, Robert; Kulmanov, Maxat; Boudellioua, Imane; Politano, Gianfranco; Di Carlo, Stefano; Benso, Alfredo; Hakala, Kai; Ginter, Filip; Mehryary, Farrokh; Kaewphan, Suwisa; Bjorne, Jari; Moen, Hans; Tolvanen, Martti E. E.; Salakoski, Tapio; Kihara, Daisuke; Jain, Aashish; Smuc, Tomislav; Altenhoff, Adrian; Ben-Hur, Asa; Rost, Burkhard; Brenner, Steven E.; Orengo, Christine A.; Jeffery, Constance J.; Bosco, Giovanni; Hogan, Deborah A.; Martin, Maria J.; O'Donovan, Claire; Mooney, Sean D.; Greene, Casey S.; Radivojac, Predrag; Friedberg, Iddo (2019)
    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.
  • Pavel, Alisa; Saarimäki, Laura A.; Möbus, Lena; Federico, Antonio; Serra, Angela; Greco, Dario (2022)
    Big Data pervades nearly all areas of life sciences, yet the analysis of large integrated data sets remains a major challenge. Moreover, the field of life sciences is highly fragmented and, consequently, so is its data, knowledge, and standards. This, in turn, makes integrated data analysis and knowledge gathering across sub-fields a demanding task. At the same time, the integration of various research angles and data types is crucial for modelling the complexity of organisms and biological processes in a holistic manner. This is especially valid in the context of drug development and chemical safety assessment where computational methods can provide solutions for the urgent need of fast, effective, and sustainable approaches. At the same time, such computational methods require the development of methodologies suitable for an inte-grated and data centred Big Data view. Here we discuss Knowledge Graphs (KG) as a solution to a data centred analysis approach for drug and chemical development and safety assessment. KGs are knowledge bases, data analysis engines, and knowledge discovery systems all in one, allowing them to be used from simple data retrieval, over meta-analysis to complex predictive and knowledge discovery systems. Therefore, KGs have immense potential to advance the data centred approach, the re-usability, and infor-mativity of data. Furthermore, they can improve the power of analysis, and the complexity of modelled processes, all while providing knowledge in a natively human understandable network data model. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (