Article
Genetics & Heredity
Stephanie Best, Janet C. Long, Jeffrey Braithwaite, Natalie Taylor
Summary: Clinical genomics requires collaboration between physicians, laboratory scientists, and genetic professionals. Understanding the underlying processes from the perspective of nongenetic physicians new to the field is important for scaling up genomics. Through interviews with nongenetic physicians using clinical genomics, a process map with 7 steps was used to identify adaptable components for scaling up clinical genomics.
GENETICS IN MEDICINE
(2023)
Article
Environmental Sciences
Aleksandra Sander, Ana Petracic, Iva Zokic, Domagoj Vrsaljko
Summary: Biodiesel produced from waste feedstocks has a significant role in addressing climate change, waste disposal, and energy demand. Research on extractive deacidification with deep eutectic solvents provides valuable insights into the process, with experimental data and validation of a working hypothesis.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Plant Sciences
Osval Antonio Montesinos-Lopez, Abelardo Montesinos-Lopez, Carlos Moises Hernandez-Suarez, Jose Alberto Barron-Lopez, Jose Crossa
Summary: Deep learning is revolutionizing artificial intelligence systems, surpassing human abilities in tasks such as image classification and computer vision. Its application in genomic selection has significant implications for plant breeding, accelerating the revolution in this field.
Article
Medical Informatics
Yucong Lin, Jia Li, Huan Xiao, Lujie Zheng, Ying Xiao, Hong Song, Jingfan Fan, Deqiang Xiao, Danni Ai, Tianyu Fu, Feifei Wang, Han Lv, Jian Yang
Summary: This article introduces an automatic literature screening method based on artificial intelligence technology - the PAJO model. The PAJO model utilizes the pre-trained BERT model to analyze text and journal features, treating article screening as a classification problem. Experimental results demonstrate that the PAJO model outperforms existing baseline models in screening high-quality articles and significantly improves the efficiency of clinical practice guideline development.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Saad Mohamad, Hamad Alamri, Abdelhamid Bouchachia
Summary: This paper proposes a unified distributed and parallel implementation of stochastic gradient descent (SGD) called DPSGD, which combines asynchronous distribution and lock-free parallelism to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied and empirical results validate its theoretical findings, showing its potential gains in terms of convergence speed and performance.
Article
Optics
Akhil Kumar, Arvind Kalia, Kinshuk Verma, Akashdeep Sharma, Manisha Kaushal
Summary: Researchers introduced a novel dataset for face mask detection that includes a large number of images and annotations, making significant contributions to various mask classification and detection tasks. Through testing with eight variants of the YOLO algorithm on the dataset, it was found that original YOLO v4 and tiny YOLO v4 performed the best.
Review
Engineering, Chemical
Giuseppe Sanzone, Jinlong Yin, Hailin Sun
Summary: This review introduces the latest progress on three types of cluster sources with the most promising potential for scale-up, including sputtering gas aggregation source, pulsed microplasma cluster source, and matrix assembly cluster source. These new methods are expected to address the low throughput and constraints in cluster material synthesis.
FRONTIERS OF CHEMICAL SCIENCE AND ENGINEERING
(2021)
Article
Genetics & Heredity
Stephanie Best, Helen Brown, Sebastian Lunke, Chirag Patel, Jason Pinner, Christopher P. Barnett, Meredith Wilson, Sarah A. Sandaradura, Belinda McClaren, Gemma R. Brett, Jeffrey Braithwaite, Zornitza Stark
Summary: By utilizing implementation science principles, we identified the importance of networks, leadership, culture, and the relative advantage of ultra-rapid genomics in caring for critically ill children. While clinical geneticists focused on intervention characteristics, intensivists emphasized the importance of access to knowledge. Tailoring support based on professional role and implementation phase is essential to maximize the potential of ultra-rapid genomic testing in improving patient care.
NPJ GENOMIC MEDICINE
(2021)
Article
Public, Environmental & Occupational Health
Jacqueline Coore-Hall, Joanne Smith, Melissa Kelly, Helen Baker-Henningham, Susan Chang, Susan Walker
Summary: Sustainable implementation of early childhood programs requires adaptable and scalable resources and methods. Active and effective monitoring, evaluation and learning process enables programs to be responsive to demands. The Reach Up: Early Childhood Parenting program has been adapted based on feedback from key informants, leading to modifications in program processes, materials and resources.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Agricultural Engineering
Alun L. James, William T. Perkins, Jones Sian, Damon Hammond, Edward M. Hodgson
Summary: Metals discharged from abandoned mines are a major source of pollution worldwide, and low-cost remediation methods are needed. This study examines the effects of scaling up biochar production on its quality, and finds that the performance of biochar decreases when tested in the field.
BIORESOURCE TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Te-Tien Ku, Chia-Hung Lin, Chao-Shun Chen, Yih-Der Lee, Jheng-Lun Jiang, Sing-Jia Tzeng, Chen-Min Chan
Summary: With the increase in distributed energy resources (DER), utilities have faced challenges in limiting the hosting capacities of DER installations on distribution feeders. A distribution static synchronous compensator (DSTATCOM) is a power electronic device that provides flexible and reliable voltage control and power quality improvement to the distribution grid by injecting or absorbing reactive power. The development of a distributed energy resources management system (DERMS) enables effective control of DSTATCOM, allowing for increased hosting capacity and mitigation of overvoltage issues. Tests conducted on a feeder belonging to Taiwan Power Company (Taipower) demonstrate the effectiveness of DSTATCOM in improving overvoltage problems by regulating voltage/reactive power (Volt/VAR) control as DER output increases.
Article
Chemistry, Multidisciplinary
Noha Khalil Mahdy, Mousa El-Sayed, Saif El -Din Al-Mofty, Abdalla Mohamed, Ali H. Karaly, Mehrez E. El-Naggar, Hassan Nageh, Wessam A. Sarhan, Hassan Mohamed El -Said Azzazy
Summary: This study examines the utilization of metal oxide nanoparticles in commercial products and compares four synthesis methods. The automated mechanochemical method shows advantages in yield, energy, and time, and is chosen to synthesize low cytotoxicity CuO NPs for the production of washable antimicrobial face masks on cotton fabrics.
Article
Computer Science, Information Systems
Quan Peng, Shan Wang
Summary: In this paper, a multi-application scheduling algorithm named MASA is designed based on deep reinforcement learning. It uses a neural network scheduler and a heuristic scheduler for task prioritization and task mapping to solve the processor resource allocation problem. Experimental results indicate that MASA outperforms other scheduling algorithms in terms of performance.
Article
Plant Sciences
Ashley M. Earley, Andries A. Temme, Christopher R. Cotter, John M. Burke
Summary: This study explores the variation and covariation patterns of leaf anatomical traits in cultivated sunflower and analyzes their genetic architecture through genome-wide association analysis. The results reveal significant correlations between different leaf traits that are consistent with functional relationships. Principal component analysis separates correlated traits into several major axes with significant genetic associations. These findings provide insights into the genetic basis of leaf trait covariation and suggest potential targets for modifying leaf anatomical traits in sunflower.
Review
Environmental Sciences
Fatemeh Ghobadi, Doosun Kang
Summary: With the rapid development of machine learning and data management, machine learning applications have expanded across all engineering disciplines. Due to the importance of global water resources management in the remaining years of this century, much research has focused on the application of machine learning strategies in integrated water resources management. Therefore, a comprehensive and well-organized review of this research is needed. This overview divides the core fundamentals, major applications, and ongoing issues into two sections to accommodate the interests of artificial intelligence and the unresolved issues of machine learning in water resources management.
Article
Biochemistry & Molecular Biology
Fergal J. Martin, M. Ridwan Amode, Alisha Aneja, Olanrewaju Austine-Orimoloye, Andrey G. Azov, If Barnes, Arne Becker, Ruth Bennett, Andrew Berry, Jyothish Bhai, Simarpreet Kaur Bhurji, Alexandra Bignell, Sanjay Boddu, Paulo R. Branco Lins, Lucy Brooks, Shashank Budhanuru Ramaraju, Mehrnaz Charkhchi, Alexander Cockburn, Luca Da Rin Fiorretto, Claire Davidson, Kamalkumar Dodiya, Sarah Donaldson, Bilal El Houdaigui, Tamara El Naboulsi, Reham Fatima, Carlos Garcia Giron, Thiago Genez, Gurpreet S. Ghattaoraya, Jose Gonzalez Martinez, Cristi Guijarro, Matthew Hardy, Zoe Hollis, Thibaut Hourlier, Toby Hunt, Mike Kay, Vinay Kaykala, Tuan Le, Diana Lemos, Diego Marques-Coelho, Jose Carlos Marugan, Gabriela Alejandra Merino, Louisse Paola Mirabueno, Aleena Mushtaq, Syed Nakib Hossain, Denye N. Ogeh, Manoj Pandian Sakthivel, Anne Parker, Malcolm Perry, Ivana Pilizota, Irina Prosovetskaia, Jose G. Perez-Silva, Ahamed Imran Abdul Salam, Nuno Saraiva-Agostinho, Helen Schuilenburg, Dan Sheppard, Swati Sinha, Botond Sipos, William Stark, Emily Steed, Ranjit Sukumaran, Dulika Sumathipala, Marie-Marthe Suner, Likhitha Surapaneni, Kyosti Sutinen, Michal Szpak, Francesca Floriana Tricomi, David Urbina-Gomez, Andres Veidenberg, Thomas A. Walsh, Brandon Walts, Elizabeth Wass, Natalie Willhoft, Jamie Allen, Jorge Alvarez-Jarreta, Marc Chakiachvili, Bethany Flint, Stefano Giorgetti, Leanne Haggerty, Garth R. Ilsley, Jane E. Loveland, Benjamin Moore, Jonathan M. Mudge, John Tate, David Thybert, Stephen J. Trevanion, Andrea Winterbottom, Adam Frankish, Sarah E. Hunt, Magali Ruffier, Fiona Cunningham, Sarah Dyer, Robert D. Finn, Kevin L. Howe, Peter W. Harrison, Andrew D. Yates, Paul Flicek
Summary: Ensembl has been providing high-quality genomic resources for vertebrates and model organisms for over 20 years. With the increase in high-quality reference genomes and the development of pangenome representations, Ensembl aims to support downstream research by creating high-quality annotations, tools, and services for species across the tree of life. This report highlights Ensembl's resources for popular reference genomes, the growing annotations, updates to the Variant Effect Predictor, protein structure predictions, and the beta release of their new website.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Genetics & Heredity
Eva Lenassi, Ana Carvalho, Anja Thormann, Liam Abrahams, Gavin Arno, Tracy Fletcher, Claire Hardcastle, Javier Lopez, Sarah E. Hunt, Patrick Short, Panagiotis Sergouniotis, Michel Michaelides, Andrew Webster, Fiona Cunningham, Simon C. Ramsden, Dalia Kasperaviciute, David R. Fitzpatrick, Graeme C. Black, Jamie M. Ellingford
Summary: EyeG2P is a publicly available database and web application designed for efficient variant prioritization for individuals with inherited ophthalmic conditions. It significantly increases precision compared to routine diagnostic approaches and reduces the number of variants for analysis in whole genome sequencing while maintaining high diagnostic yield.
JOURNAL OF MEDICAL GENETICS
(2023)
Article
Biochemical Research Methods
Zhixu Ni, Michele Wolk, Geoff Jukes, Karla Mendivelso Espinosa, Robert Ahrends, Lucila Aimo, Jorge Alvarez-Jarreta, Simon Andrews, Robert Andrews, Alan Bridge, Geremy C. Clair, Matthew J. Conroy, Eoin Fahy, Caroline Gaud, Laura Goracci, Juergen Hartler, Nils Hoffmann, Dominik Kopczyinki, Ansgar Korf, Andrea F. Lopez-Clavijo, Adnan Malik, Jacobo Miranda Ackerman, Martijn R. Molenaar, Claire O'Donovan, Tomas Pluskal, Andrej Shevchenko, Denise Slenter, Gary Siuzdak, Martina Kutmon, Hiroshi Tsugawa, Egon L. Willighagen, Jianguo Xia, Valerie B. O'Donnell, Maria Fedorova
Summary: Progress in mass spectrometry lipidomics has led to a rapid increase in research in biology and biomedicine, generating large datasets that require sophisticated solutions for automated data processing. To address this issue, various software tools have been developed, but researchers often face difficulties in choosing the most suitable approach, resulting in inefficient and time-consuming ad hoc testing.
Article
Biochemistry & Molecular Biology
Adam Frankish, Silvia Carbonell-Sala, Mark Diekhans, Irwin Jungreis, Jane E. Loveland, Jonathan M. Mudge, Cristina Sisu, James C. Wright, Carme Arnan, If Barnes, Abhimanyu Banerjee, Ruth Bennett, Andrew Berry, Alexandra Bignell, Carles Boix, Ferriol Calvet, Daniel Cerdan-Velez, Fiona Cunningham, Claire Davidson, Sarah Donaldson, Cagatay Dursun, Reham Fatima, Stefano Giorgetti, Carlos Garcia Giron, Jose Manuel Gonzalez, Matthew Hardy, Peter W. Harrison, Thibaut Hourlier, Zoe Hollis, Toby Hunt, Benjamin James, Yunzhe Jiang, Rory Johnson, Mike Kay, Julien Lagarde, Fergal J. Martin, Laura Martinez Gomez, Surag Nair, Pengyu Ni, Fernando Pozo, Vivek Ramalingam, Magali Ruffier, Bianca M. Schmitt, Jacob M. Schreiber, Emily Steed, Marie-Marthe Suner, Dulika Sumathipala, Irina Sycheva, Barbara Uszczynska-Ratajczak, Elizabeth Wass, Yucheng T. Yang, Andrew Yates, Zahoor Zafrulla, Jyoti S. Choudhary, Mark Gerstein, Roderic Guigo, Tim J. P. Hubbard, Manolis Kellis, Anshul Kundaje, Benedict Paten, Michael L. Tress, Paul Flicek
Summary: GENCODE provides high quality gene and transcript annotation for the human and mouse genomes, supported by experimental data, serving as a reference for genome biology and clinical genomics. The consortium generates data, develops tools and carries out analyses to support the identification and annotation of transcript structures and their function.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Elliot Sollis, Abayomi Mosaku, Ala Abid, Annalisa Buniello, Maria Cerezo, Laurent Gil, Tudor Groza, Osman Gunes, Peggy Hall, James Hayhurst, Arwa Ibrahim, Yue Ji, Sajo John, Elizabeth Lewis, Jacqueline A. L. MacArthur, Aoife McMahon, David Osumi-Sutherland, Kalliope Panoutsopoulou, Zoe Pendlington, Santhi Ramachandran, Ray Stefancsik, Jonathan Stewart, Patricia Whetzel, Robert Wilson, Lucia Hindorff, Fiona Cunningham, Samuel A. Lambert, Michael Inouye, Helen Parkinson, Laura W. Harris
Summary: The NHGRI-EBIGWAS Catalog is a knowledgebase that provides comprehensive and standardized genome-wide association study (GWAS) data. By updating software, expanding the scope of the database, and increasing community outreach, the catalog has improved the quality and quantity of data, as well as enhanced interoperability with other resources.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Typhaine Paysan-Lafosse, Matthias Blum, Sara Chuguransky, Tiago Grego, Beatriz Lazaro Pinto, Gustavo A. Salazar, Maxwell L. Bileschi, Peer Bork, Alan Bridge, Lucy Colwell, Julian Gough, Daniel H. Haft, Ivica Letunic, Aron Marchler-Bauer, Huaiyu Mi, Darren A. Natale, Christine A. Orengo, Arun P. Pandurangan, Catherine Rivoire, Christian J. A. Sigrist, Ian Sillitoe, Narmada Thanki, Paul D. Thomas, Silvio C. E. Tosatto, Cathy H. Wu, Alex Bateman
Summary: The InterPro database has been updated with new data content and website features, providing a more user-friendly access to protein sequence classification and functional domain identification. It has also integrated features from the retiring Pfam website and developed a card game to engage the non-scientific community. Furthermore, the database explores the benefits and challenges of using artificial intelligence for protein structure prediction.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Alex Bateman, Maria-Jesus Martin, Sandra Orchard, Michele Magrane, Shadab Ahmad, Emanuele Alpi, Emily H. Bowler-Barnett, Ramona Britto, Austra Cukura, Paul Denny, Tunca Dogan, ThankGod Ebenezer, Jun Fan, Penelope Garmiri, Leonardo Jose da Costa Gonzales, Emma Hatton-Ellis, Abdulrahman Hussein, Alexandr Ignatchenko, Giuseppe Insana, Rizwan Ishtiaq, Vishal Joshi, Dushyanth Jyothi, Swaathi Kandasaamy, Antonia Lock, Aurelien Luciani, Marija Lugaric, Jie Luo, Yvonne Lussi, Alistair MacDougall, Fabio Madeira, Mahdi Mahmoudy, Alok Mishra, Katie Moulang, Andrew Nightingale, Sangya Pundir, Guoying Qi, Shriya Raj, Pedro Raposo, Daniel L. Rice, Rabie Saidi, Rafael Santos, Elena Speretta, James Stephenson, Prabhat Totoo, Edward Turner, Nidhi Tyagi, Preethi Vasudev, Kate Warner, Xavier Watkins, Hermann Zellner, Alan J. Bridge, Lucila Aimo, Ghis-laine Argoud-Puy, Andrea H. Auchincloss, Kristian B. Axelsen, Parit Bansal, Delphine Baratin, Teresa M. Batista Neto, Marie-Claude Blatter, Jerven T. Bolleman, Emmanuel Boutet, Lionel Breuza, Blanca Cabrera Gil, Cristina Casals-Casas, Kamal Chikh Echioukh, Elisabeth Coudert, Beatrice Cuche, Edouard de Castro, Anne Estreicher, Maria L. Famiglietti, Marc Feuermann, Elisabeth Gasteiger, Pascale Gaudet, Sebastien Gehant, Vivienne Gerritsen, Arnaud Gos, Nadine Gruaz, Chantal Hulo, Nevila Hyka-Nouspikel, Florence Jungo, Arnaud Kerhornou, Philippe Le Mercier, Damien Lieberherr, Patrick Masson, Anne Morgat, Venkatesh Muthukrishnan, Salvo Paesano, Ivo Pedruzzi, Sandrine Pilbout, Lucille Pourcel, Sylvain Poux, Monica Pozzato, Manuela Pruess, Nicole Redaschi, Catherine Rivoire, Christian J. A. Sigrist, Karin Sonesson, Cecilia N. Arighi, Leslie Armin-ski, Chuming Chen, Yongxing Chen, Hongzhan Huang, Kati Laiho, Peter McGarvey, Darren A. Natale, Karen Ross, C. R. Vinayaka, Qinghua Wang, Yuqi Wang, Jian Zhang, Hema Bye-A-Jee, Rossana Zaru, Shyamala Sundaram, Cathy H. Wu
Summary: The UniProt Knowledgebase aims to provide comprehensive, high-quality, and freely accessible protein sequences annotated with functional information. The database has expanded its data processing pipeline and website to accommodate the increasing information content, with over 227 million sequences and plans to include a reference proteome for each taxonomic group. Detailed annotations are extracted from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations from automated systems. The new website, https://www.uniprot.org/, offers enhanced user experience and easy access to data, including AlphaFold structures and improved protein subcellular localization visualizations.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Cell Biology
Maria C. Costanzo, Marcin von Grotthuss, Jeffrey Massung, Dongkeun Jang, Lizz Caulkins, Ryan Koesterer, Clint Gilbert, Ryan P. Welch, Parul Kudtarkar, Quy Hoang, Andrew P. Boughton, Preeti Singh, Ying Sun, Marc Duby, Annie Moriondo, Trang Nguyen, Patrick Smadbeck, Benjamin R. Alexander, MacKenzie Brandes, Mary Carmichael, Peter Dornbos, Todd Green, Kenneth C. Huellas-Bruskiewicz, Yue Ji, Alexandria Kluge, Aoife C. McMahon, Josep M. Mercader, Oliver Ruebenacker, Sebanti Sengupta, Dylan Spalding, Daniel Taliun, Philip Smith, Melissa K. Thomas, Beena Akolkar, M. Julia Brosnan, Andriy Cherkas, Audrey Y. Chu, Eric B. Fauman, Caroline S. Fox, Tania Nayak Kamphaus, Melissa R. Miller, Lynette Nguyen, Afshin Parsa, Dermot F. Reilly, Hartmut Ruetten, David Wholley, Norann A. Zaghloul, Goncalo R. Abecasis, David Altshuler, Thomas M. Keane, Mark I. McCarthy, Kyle J. Gaulton, Jose C. Florez, Michael Boehnke, Noel P. Burtt, Jason Flannick
Summary: This study aims to make the Type 2 Diabetes Knowledge Portal (T2DKP) more accessible and useful to both new and existing users. It evaluates the comprehensiveness of T2DKP by comparing its datasets with other repositories, guides researchers unfamiliar with human genetic data on how to interpret and use the data through T2DKP, and discusses the importance of democratizing access to complex disease genetic results.
Article
Genetics & Heredity
Suzi A. Aleksander, James Balhoff, Seth Carbon, J. Michael Cherry, Harold J. Drabkin, Dustin Ebert, Marc Feuermann, Pascale Gaudet, Nomi L. Harris, David P. Hill, Raymond Lee, Huaiyu Mi, Sierra Moxon, Christopher J. Mungall, Anushya Muruganugan, Tremayne Mushayahama, Paul W. Sternberg, Paul D. Thomas, Kimberly Van Auken, Jolene Ramsey, Deborah A. Siegele, Rex L. Chisholm, Petra Fey, Maria Cristina Aspromonte, Maria Victoria Nugnes, Federica Quaglia, Silvio Tosatto, Michelle Giglio, Suvarna Nadendla, Giulia Antonazzo, Helen Attrill, Gil dos Santos, Steven Marygold, Victor Strelets, Christopher J. Tabone, Jim Thurmond, Pinglei Zhou, Saadullah H. Ahmed, Praoparn Asanitthong, Diana Luna Buitrago, Meltem N. Erdol, Matthew C. Gage, Mohamed Ali Kadhum, Kan Yan Chloe Li, Miao Long, Aleksandra Michalak, Angeline Pesala, Armalya Pritazahra, Shirin C. C. Saverimuttu, Renzhi Su, Kate E. Thurlow, Ruth C. Lovering, Colin Logie, Snezhana Oliferenko, Judith Blake, Karen Christie, Lori Corbani, Mary E. Dolan, Dmitry Sitnikov, Cynthia Smith, Alayne Cuzick, James Seager, Laurel Cooper, Justin Elser, Pankaj Jaiswal, Parul Gupta, Sushma Naithani, Manuel Lera-Ramirez, Kim Rutherford, Valerie Wood, Jeffrey L. De Pons, Melinda R. Dwinell, G. Thomas Hayman, Mary L. Kaldunski, Anne E. Kwitek, Stanley J. F. Laulederkind, Marek A. Tutaj, Mahima Vedi, Shur-Jen Wang, Peter D'Eustachio, Lucila Aimo, Kristian Axelsen, Alan Bridge, Nevila Hyka-Nouspikel, Anne Morgat, Stacia R. Engel, Kalpana Karra, Stuart R. Miyasato, Robert S. Nash, Marek S. Skrzypek, Shuai Weng, Edith D. Wong, Erika Bakker, Tanya Z. Berardini, Leonore Reiser, Andrea Auchincloss, Ghislaine Argoud-Puy, Marie-Claude Blatter, Emmanuel Boutet, Lionel Breuza, Cristina Casals-Casas, Elisabeth Coudert, Anne Estreicher, Maria Livia Famiglietti, Arnaud Gos, Nadine Gruaz-Gumowski, Chantal Hulo, Florence Jungo, Philippe Le Mercier, Damien Lieberherr, Patrick Masson, Ivo Pedruzzi, Lucille Pourcel, Sylvain Poux, Catherine Rivoire, Shyamala Sundaram, Alex Bateman, Emily Bowler-Barnett, Hema Bye-A-Jee, Paul Denny, Alexandr Ignatchenko, Rizwan Ishtiaq, Antonia Lock, Yvonne Lussi, Michele Magrane, Maria J. Martin, Sandra Orchard, Pedro Raposo, Elena Speretta, Nidhi Tyagi, Kate Warner, Rossana Zaru, Alexander D. Diehl, Juancarlos Chan, Stavros Diamantakis, Daniela Raciti, Magdalena Zarowiecki, Malcolm Fisher, Christina James-Zorn, Virgilio Ponferrada, Aaron Zorn, Sridhar Ramachandran, Leyla Ruzicka, Monte Westerfield
Summary: The Gene Ontology (GO) knowledgebase is a comprehensive resource that provides information about the functions of genes and gene products. It covers a wide range of organisms and receives updates from a consortium of scientists. The knowledgebase consists of three components: GO, which describes gene functionality; GO annotations, which provide evidence-supported statements about gene products; and GO-CAMs, which are models of molecular pathways. The knowledgebase is continuously updated and reviewed, and guidance is provided to users on how to make the best use of the data.
Article
Biochemistry & Molecular Biology
Adrian Altenhoff, Amos Bairoch, Parit Bansal, Delphine Baratin, Frederic Bastian, Jerven Bolleman, Alan Bridge, Frederic Burdet, Katrin Crameri, Jerome Dauvillier, Christophe Dessimoz, Sebastien Gehant, Natasha Glover, Kristin Gnodtke, Catherine Hayes, Mark Ibberson, Evgenia Kriventseva, Dmitry Kuznetsov, Frederique Lisacek, Florence Mehl, Tarcisio Mendes de Farias, Pierre-Andre Michel, Sebastien Moretti, Anne Morgat, Sabine Osterle, Marco Pagni, Nicole Redaschi, Marc Robinson-Rechavi, Kasun Samarasinghe, Ana-Claudia Sima, Damian Szklarczyk, Orlin Topalov, Vasundra Toure, Deepak Unni, Christian von Mering, Julien Wollbrett, Monique Zahn-Zabal, Evgeny Zdobnov
Summary: This paper introduces the SIB Swiss Institute of Bioinformatics and its 11 databases, which provide semantically enriched data according to the FAIR principles. It also discusses the Swiss Personalized Health Network initiative and how it uses semantic enrichment to manipulate data. Examples and the use of SPARQL query language are provided to show how the existing SIB knowledge graphs can address complex biological or clinical questions.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Oncology
John H. Lockhart, Hayley D. Ackerman, Kyubum Lee, Mahmoud Abdalah, Andrew John Davis, Nicole Hackel, Theresa A. Boyle, James Saller, Aysenur Keske, Kay Hanggi, Brian Ruffell, Olya Stringfield, W. Douglas Cress, Aik Choon Tan, Elsa R. Flores
Summary: Preclinical genetically engineered mouse models (GEMMs) of lung adenocarcinoma are valuable for studying tumor formation, progression, and therapeutic resistance. To improve histological analysis in these models, researchers developed GLASS-AI, a machine learning tool for grading, segmenting, and analyzing tumors. GLASS-AI showed agreement with expert raters and revealed previously unreported intratumor heterogeneity. Integration of immunohistochemical staining with GLASS-AI analysis identified dysregulation of Mapk/Erk signaling in high-grade lung adenocarcinomas. This study demonstrates the usefulness of GLASS-AI and the power of combining machine learning and molecular biology techniques for cancer research.
NPJ PRECISION ONCOLOGY
(2023)
Article
Biochemical Research Methods
Elisabeth Coudert, Sebastien Gehant, Edouard de Castro, Monica Pozzato, Delphine Baratin, Teresa Neto, Christian J. A. Sigrist, Nicole Redaschi, Alan Bridge
Summary: This study aims to provide high-quality annotations of binding sites for biologically relevant ligands in UniProtKB using the ChEBI chemical ontology. The researchers developed improved search and query facilities for these binding sites and used stable unique identifiers from ChEBI as reference vocabulary for the annotations. The annotations are freely available for querying and downloading through the UniProt website, REST API, SPARQL endpoint, and FTP site.
Article
Biochemical Research Methods
Ling Luo, Chih-Hsuan Wei, Po-Ting Lai, Robert Leaman, Qingyu Chen, Zhiyong Lu
Summary: Biomedical named entity recognition (BioNER) aims to automatically identify biomedical entities in natural language text, providing a necessary foundation for downstream text mining tasks and applications. Due to the expensive and domain-specific expertise required for manual annotation of training data, current BioNER approaches suffer from data scarcity and limitations in generalizability and entity coverage. In this paper, we propose an all-in-one (AIO) scheme that utilizes external annotated resources to enhance the accuracy and stability of BioNER models. We introduce AIONER, a general-purpose BioNER tool based on cutting-edge deep learning and our AIO scheme, and demonstrate its effectiveness, robustness, and advantages over existing methods on 14 BioNER benchmark tasks and three independent tasks.
Meeting Abstract
Endocrinology & Metabolism
Valerie Schwitzgebel, Ingrida Stankute, Cedric Howald, Jean-Louis Blouin, Rasa Verkauskiene, Ioannis Xenarios
HORMONE RESEARCH IN PAEDIATRICS
(2023)
Article
Biochemical Research Methods
Chih-Hsuan Wei, Ling Luo, Rezarta Islamaj, Po-Ting Lai, Zhiyong Lu
Summary: Gene name normalization is a complex task in biomedical text mining research. GNorm2, an advanced tool, uses deep learning methods to achieve the highest levels of accuracy and efficiency in gene recognition and normalization.