Frequent contiguous pattern mining over biological sequences of protein misfolded diseases
Autor: | Mohammad Shahedul Islam, Md. Abul Kashem Mia, Pranab Kumar Dhar, Mohammad S. Rahman, Takeshi Koshiba, Mohammad Shamsul Arefin |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Rhodopsin
QH301-705.5 media_common.quotation_subject Computer applications to medicine. Medical informatics R858-859.7 Biochemistry Structural Biology Gratitude Humans Wife Frequent pattern Disease Amino Acid Sequence Sociology Amino Acids Biology (General) Molecular Biology media_common Research Applied Mathematics Kamal Subject (documents) NASA Chief Scientist Computer Science Applications Management Amino acid Association rule Subject-matter expert Schedule (workplace) Work (electrical) Protein sequence Retinitis Pigmentosa Protein misfolding |
Zdroj: | BMC Bioinformatics, Vol 22, Iss 1, Pp 1-28 (2021) BMC Bioinformatics |
ISSN: | 1471-2105 |
Popis: | BackgroundProteins are integral part of all living beings, which are building blocks of many amino acids. To be functionally active, amino acids chain folds up in a complex way to give each protein a unique 3D shape, where a minor error may cause misfolded structure. Genetic disorder diseases i.e.Alzheimer, Parkinson,etc. arise due to misfolding in protein sequences. Thus, identifying patterns of amino acids is important for inferring protein associated genetic diseases. Recent studies in predicting amino acids patterns focused on only simple protein misfolded disease i.e.Chromaffin Tumor, by association rule mining. However, more complex diseases are yet to be attempted. Moreover, association rules obtained by these studies were not verified by usefulness measuring tools.ResultsIn this work, we analyzed protein sequences associated with complex protein misfolded diseases (i.e.Sickle Cell Anemia, Breast Cancer, Cystic Fibrosis, Nephrogenic Diabetes Insipidus,andRetinitis Pigmentosa 4) by association rule mining technique and objective interestingness measuring tools. Experimental results show the effectiveness of our method.ConclusionAdopting quantitative experimental methods, this work can form more reliable, useful and strong association rules i. e. dominating patterns of amino acid of complex protein misfolded diseases. Thus, in addition to usual applications, the identified patterns can be more useful in discovering medicines for protein misfolded diseases and thereby may open up new opportunities in medical science to handle genetic disorder diseases. |
Databáze: | OpenAIRE |
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