A5021103092- Bioinformatics and Genomic Networks
- Biomedical Text Mining and Ontologies
- Alzheimer's disease research and treatments
- Parkinson's Disease Mechanisms and Treatments
- Topic Modeling
- Forensic and Genetic Research
- Protein Structure and Dynamics
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Ethics in Clinical Research
- RNA and protein synthesis mechanisms
- Biochemical and Structural Characterization
- Domain Adaptation and Few-Shot Learning
- Genetics, Bioinformatics, and Biomedical Research
- Health Systems, Economic Evaluations, Quality of Life
- Dementia and Cognitive Impairment Research
- Machine Learning in Healthcare
- Epilepsy research and treatment
- Genomics and Phylogenetic Studies
- Microbial Metabolic Engineering and Bioproduction
- Asthma and respiratory diseases
- Genomics and Rare Diseases
- Computational Drug Discovery Methods
- Dermatology and Skin Diseases
- Genetic Neurodegenerative Diseases
- Molecular Biology Techniques and Applications
UCB Pharma (Belgium)
2019-2025
UCB Pharma (United Kingdom)
2015-2024
University of Manchester
1999
University College London
1997-1999
Pfizer (United Kingdom)
1997
Daresbury Laboratory
1997
University of Leeds
1997
PRINTS is a diagnostic collection of protein fingerprints. Fingerprints exploit groups motifs to build characteristic family signatures, offering improved reliability over single-motif approaches by virtue the mutual context provided motif neighbours. Around 1000 fingerprints have now been created and stored in PRINTS. The September 1998 release (version 20.0), encodes approximately 5700 motifs, covering range globular membrane proteins, modular polypeptides so on. database accessible via...
Rare diseases pose significant challenges in diagnosis and treatment due to their low prevalence heterogeneous clinical presentations. Unstructured notes contain valuable information for identifying rare diseases, but manual curation is time-consuming prone subjectivity. This study aims develop a hybrid approach combining dictionary-based natural language processing (NLP) tools with large models (LLMs) improve disease identification from unstructured reports.
Abstract MOTIVATION: By identifying an unknown gene or protein as a member of known family, we can infer wealth previously compiled information pertinent to that family and its members. RESULTS: This paper introduces method classifies sequences using familial definitions from the PRINTS database, allowing progress be made with identification distant evolutionary relationships. The approach makes use contextual inherent in multiple-motif method, has power identify hitherto unidentified...
Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization mechanisms underlying Parkinson's disease. In area research, there is a pressing need to integrate various pieces information into meaningful context presumed disease mechanism(s). Disease ontologies provide novel means for organizing, integrating, standardizing knowledge domains specific compact, formalized computer-readable form serve as reference exchange or...
The evaluation and management of first-time seizure-like events in children can be difficult because these episodes are not always directly observed might epileptic seizures or other conditions (seizure mimics). We aimed to evaluate whether machine learning models using real-world data could predict seizure recurrence after an initial event. This retrospective cohort study compared trained evaluated on two separate datasets between Jan 1, 2010, 2020: electronic medical records (EMRs) at...
Biomarker discovery, development, and validation are reliant on large-scale analyses of high-quality samples data. Currently, significant quantities data have been generated by European studies Alzheimer's disease (AD) other neurodegenerative diseases (NDD), representing a valuable resource for developing biomarkers to support early detection disease, treatment monitoring, patient stratification. However, discovery of, access to, sharing from AD NDD research hindered both silos that limit...
Abstract One of the visions precision medicine has been to re-define disease taxonomies based on molecular characteristics rather than phenotypic evidence. However, achieving this goal is highly challenging, specifically in neurology. Our contribution a machine-learning joint subtyping Alzheimer’s (AD) and Parkinson’s Disease (PD), genetic burden 15 mechanisms comprising 27 proteins (e.g. APOE) that have described both diseases. We demonstrate our AD/PD clustering using combination sparse...
PRINTS is a compendium of protein motif fingerprints derived from the OWL composite sequence database. Fingerprints are groups motifs within alignments whose conserved nature allows them to be used as signatures family membership. inherently offer improved diagnostic reliability over single methods by virtue mutual context provided neighbors. To date, 650 have been constructed and stored in PRINTS, size which has doubled last 2 years. The current version, 14.0, encodes 3500 motifs, covering...
Abstract SUMMARY: An implementation of BLAST for searching the PRINTS database is presented. The interface allows submission either protein or DNA queries, and returns familiar form output, but modified by means direct links both to familial discriminators in fingerprint profile visualization software. server thus couples rapidity with sensitivity diagnoses, providing alternative perspectives on a given query. AVAILABILITY: http://www.biochem.ucl. ac.uk/cgi-bin/wright/printsBLAST.cgi
Abstract Background Although advances in the understanding of neurodegenerative diseases (NDDs) have led to improvements classification and diagnosis most importantly new therapies, unmet medical needs remain significant due high treatment failure rates. The AETIONOMY project funded by Innovative Medicine Initiative (IMI) aims at using multi-OMICs bioinformatics identify classifications for NDDs based on common molecular pathophysiological mechanisms view improving availability personalised...
Abstract Background Biomarker discovery, development, and validation are reliant on large‐scale analyses of high‐quality samples data. However, access, sharing data hindered both by silos that limit collaboration, complex requirements for secure, legal, ethical sharing. The European Platform Neurodegenerative Diseases (EPND) project aims to address these challenges accelerate biomarker development validation, building a scalable, sustainable platform sample In this presentation we will give...
Abstract ChemInform is a weekly Abstracting Service, delivering concise information at glance that was extracted from about 100 leading journals. To access of an article which published elsewhere, please select “Full Text” option. The original trackable via the “References”