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See detailThe BIOMarkers in Atopic Dermatitis and Psoriasis (BIOMAP) Glossary: developing a lingua franca to facilitate data harmonisation and cross-cohort analyses
Broderick, Conor; Christian, Nils; Apfelbacher, Christian et al

in British Journal of Dermatology (2021)

Dear Editor, BIOMAP (BIOMarkers in Atopic dermatitis and Psoriasis) is a large European consortium aiming to advance personalised medicine for atopic dermatitis and psoriasis by identifying biomarkers ... [more ▼]

Dear Editor, BIOMAP (BIOMarkers in Atopic dermatitis and Psoriasis) is a large European consortium aiming to advance personalised medicine for atopic dermatitis and psoriasis by identifying biomarkers which predict therapeutic response and disease progression. BIOMAP brings together clinicians, researchers, patient organisations and pharmaceutical industry partners and encompasses data from over 60 individual studies, including randomised clinical trials, population-based cohorts and deeply-phenotyped disease registries. The curation and harmonisation of data and bio-samples from these established studies will facilitate cross-cohort clinical and molecular analyses, increasing the potential to identify small effect estimates and to better stratify disease subtypes. This letter serves to disseminate BIOMAP's pathway to data harmonisation and will inform future collaborative research endeavours. [less ▲]

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See detailSupporting findability of COVID-19 research with large-scale text mining of scientific publications
Welter, Danielle UL; Vega Moreno, Carlos Gonzalo UL; Biryukov, Maria UL et al

Poster (2020, November 27)

When the COVID-19 pandemic hit in early 2020, a lot of research efforts were quickly redirected towards studies on SARS-CoV2 and COVID-19 disease, from the sequencing and assembly of viral genomes to the ... [more ▼]

When the COVID-19 pandemic hit in early 2020, a lot of research efforts were quickly redirected towards studies on SARS-CoV2 and COVID-19 disease, from the sequencing and assembly of viral genomes to the elaboration of robust testing methodologies and the development of treatment and vaccination strategies. At the same time, a flurry of scientific publications around SARS-CoV-2 and COVID-19 began to appear, making it increasingly difficult for researchers to stay up-to-date with latest trends and developments in this rapidly evolving field. The BioKB platform is a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles. The content of the articles is analysed and concepts from a range of contexts, including proteins, species, chemicals, diseases and biological processes are tagged based on existing dictionaries of controlled terms. Co-occurring concepts are classified based on their asserted relationship and the resulting subject-relation-object triples are stored in a publicly accessible human- and machine-readable knowledge base. All concepts in the BioKB dictionaries are linked to stable, persistent identifiers, either a resource accession such as an Ensembl, Uniprot or PubChem ID for genes, proteins and chemicals, or an ontology term ID for diseases, phenotypes and other ontology terms. In order to improve COVID-19 related text mining, we extended the underlying dictionaries to include many additional viral species (via NCBI Taxonomy identifiers), phenotypes from the Human Phenotype Ontology (HPO), COVID-related concepts including clinical and laboratory tests from the COVID-19 ontology, as well as additional diseases (DO) and biological processes (GO). We also added all viral proteins found in UniProt and gene entries from EntrezGene to increase the sensitivity of the text mining pipeline to viral data. To date, BioKB has indexed over 270’000 sentences from 21’935 publications relating to coronavirus infections, with publications dating from 1963 to 2021, 3’863 of which were published this year. We are currently working to further refine the text mining pipeline by training it on the extraction of increasingly complex relations such as protein-phenotype relationships. We are also regularly adding new terms to our dictionaries for areas where coverage is currently low, such as clinical and laboratory tests and procedures and novel drug treatments. [less ▲]

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See detailPrevalence of SARS-CoV-2 infection in the Luxembourgish population: the CON-VINCE study.
Snoeck, Chantal J.; Vaillant, Michel; Abdelrahman, Tamir et al

E-print/Working paper (2020)

BACKGROUND: After the World Health Organization declared the outbreak of coronavirus disease to be a public health emergency of international concern on January 30, 2020, the first SARS-CoV-2 infection ... [more ▼]

BACKGROUND: After the World Health Organization declared the outbreak of coronavirus disease to be a public health emergency of international concern on January 30, 2020, the first SARS-CoV-2 infection was detected in Luxembourg on February 29, 2020. Representative population-based data, including asymptomatic individuals for assessing the viral spread and immune response were, however, lacking worldwide. METHODS: Using a panel-based method, we implemented a representative sample of the Luxembourgish population based on age, gender and residency for testing for SARS-CoV-2 infection and antibody status in order to define prevalence irrespective of clinical symptoms. Participants were contacted via email to fill an online questionnaire before biosampling at local laboratories. All participants provided information related to clinical symptoms, epidemiology, socioeconomic and psychological assessments and underwent biosampling, rRT-PCR testing and serology for SARS-CoV-2. RESULTS: We included a total of 1862 individuals in our representative sample of the general Luxembourgish population. Of these, 5 individuals had a current positive result for infection with SARS-CoV-2 based on rRT-PCR. Four of these individuals were oligosymptomatic and one was asymptomatic. Overall we found a positive IgG antibody status in 35 individuals (1.97%), of which 11 reported to be tested positive by rRT-PCR for SARS-CoV-2 previously and showed in addition their IgG positive status also a positive status for IgA. Our data indicate a prevalence of 0.3% for active SARS-CoV-2 infection and an infection rate of 2.15% in the Luxembourgish population between 18 and 79 years of age. CONCLUSIONS: Luxembourgish residents show a low rate of acute infections after 7 weeks of confinement and present with an antibody profile indicative of a more recent immune response to SARS-CoV-2. All infected individuals were oligo- or asymptomatic. Bi-weekly follow-up visits over the next 2 months will inform about the viral spread by a- and oligosymptomatic carriers and the individual changes in the immune profile.Competing Interest StatementThe authors have declared no competing interest.Clinical TrialNCT04379297Funding StatementThe CON-VINCE Study is funded by the Research Fund Luxembourg (FNR; CON-VINCE) and the André Losch Foundation (Luxembourg).Author DeclarationsAll relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.YesAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesDue to ethical concerns, supporting data cannot be made openly available. [less ▲]

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See detailA New Kind of Computational Biology
Pal Chaudhuri, Parimal; Ghosh, Soumyabrata UL; Dutta, Adip et al

Book published by Springer Nature (2018)

This book reflects more than three decades of research on Cellular Automata (CA), and nearly a decade of work on the application of CA to model biological strings, which forms the foundation of 'A New ... [more ▼]

This book reflects more than three decades of research on Cellular Automata (CA), and nearly a decade of work on the application of CA to model biological strings, which forms the foundation of 'A New Kind of Computational Biology' pioneered by the start-up, CARLBio. After a brief introduction on Cellular Automata (CA) theory and functional biology, it reports on the modeling of basic biological strings with CA, starting with the basic nucleotides leading to codon and anti-codon CA models. It derives a more involved CA model of DNA, RNA, the entire translation process for amino acid formation and the evolution of protein to its unique structure and function. In subsequent chapters the interaction of Proteins with other bio-molecules is also modeled. The only prior knowledge assumed necessary is an undergraduate knowledge of computer programming and biology. [less ▲]

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See detailCellular Automata Model for Proteomics and Its Application in Cancer Immunotherapy
Ghosh, Soumyabrata UL; Chaudhuri, Parimal Pal

in Cellular Automata, Conference proceedings, ACRI 2018 (2018)

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See detailCellular Automata Model for Protein Structure Synthesis (PSS)
Ghosh, Soumyabrata UL; Maiti, Nirmalya S.; Chaudhuri, Parimal Pal

in Lecture Notes in Computer Science (2014)

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See detailCellular Automata (CA) Model for Primality Test
Maiti, Nirmalya Sundar; Ghosh, Soumyabrata UL; Chaudhuri, Parimal Pal

in Lecture Notes in Computer Science (2014)

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See detailTheory and Application of Restricted Five Neighborhood Cellular Automata (R5NCA) for Protein Structure Prediction
Ghosh, Soumyabrata UL; Maiti, Nirmalya S.; Chaudhuri, Parimal Pal

in Lecture Notes in Computer Science (2012)

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See detailRule Vector Graph (RVG) To Design Linear Time Algorithm for Identifying the Invertibility of Periodic-Boundary Three Neighborhood Cellular Automata.
Maitii, Nirmalya S.; Ghosh, Soumyabrata UL; Sikdar, Biplab K. et al

in Journal of Cellular Automata (2012), 7(4),

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See detailOn Invertible Three Neighborhood Null-Boundary Uniform Cellular Automata
Ghosh, Soumyabrata UL; Maiti, Nirmalya S.; Chaudhuri, P. Pal et al

in Complex Systems (2011), 20(1), 4

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See detailTheory and application of equal length cycle cellular automata (ELCCA) for enzyme classification
Ghosh, Soumyabrata UL; Bachhar, Tirthankar; Maiti, Nirmalya S. et al

in International Conference on Cellular Automata (2010)

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See detailProgrammable Cellular Automata (PCA) Based Advanced Encryption Standard (AES) Hardware Architecture
Maiti, Nirmalya S.; Ghosh, Soumyabrata UL; Shikdar, Biplab K. et al

in Lecture Notes in Computer Science (2010)

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See detailLinear time algorithm for identifying the invertibility of null-boundary three neighborhood cellular automata
Maiti, Nirmalya S.; Ghosh, Soumyabrata UL; Munshi, Shiladitya et al

in Complex Systems (2010), 19(1), 89

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