Journal of computational biology and bioinformatics research最新文献

{"title":"The perils of artificial intelligence in healthcare: Disease diagnosis and treatment","authors":"J. C. Lee","doi":"10.5897/JCBBR2019.0122","DOIUrl":"https://doi.org/10.5897/JCBBR2019.0122","url":null,"abstract":"For the past decade, artificial intelligence (AI) and its related technologies have made remarkable advances in marketing and business solutions based on AI-driven big data analysis of customer queries, and it, when coupled with bioinformatics, seemingly holds out great promise for use in healthcare. In reality, however, AI is still largely a buzzword when it comes to disease diagnosis and treatment. This review addresses the uncertainty of AI applications to disease diagnosis and treatment, not only pinpointing AI’s inherent algorithmic problems in dealing with non-patternable stochastic healthcare data, but also revealing the innate fallacy of identifying genetic mutations as a tool for genome-based personalized medicine. Finally, this review concludes by presenting some insights into future AI application in healthcare. \u0000 \u0000   \u0000 \u0000 Key words: Artificial intelligence, machine learning, deep learning, bioinformatics, healthcare, genomic medicine, personalized medicine, reference genome, genetic variation.","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5897/JCBBR2019.0122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46751983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theoretical and conceptual derivation of threshold phenomena and metabolic switching models in a chemostat system","authors":"Thierie Jacques","doi":"10.5897/jcbbr2018.0117","DOIUrl":"https://doi.org/10.5897/jcbbr2018.0117","url":null,"abstract":"","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5897/jcbbr2018.0117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71138344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selection of T cell epitopes from S. mansoni Sm23 protein as a vaccine construct, using Immunoinformatics approach","authors":"O. Onile, Shadrach Olaleka Fadare, G. Omitogun","doi":"10.5897/jcbbr2016.0109","DOIUrl":"https://doi.org/10.5897/jcbbr2016.0109","url":null,"abstract":"","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5897/jcbbr2016.0109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71138334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms.","authors":"James Lindesay, Tshela E Mason, William Hercules, Georgia M Dunston","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous \"thermodynamics\" characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An <i>in silico</i> analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.</p>","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4310014/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33021184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms","authors":"J. Lindesay, T. Mason, William Hercules, G. Dunston","doi":"10.5897/JCBBR2014.0102","DOIUrl":"https://doi.org/10.5897/JCBBR2014.0102","url":null,"abstract":"Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous “thermodynamics” characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71138323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.","authors":"James Lindesay, Tshela E Mason, Luisel Ricks-Santi, William Hercules, Philip Kurian, Georgia M Dunston","doi":"10.5897/jcbbr11.026","DOIUrl":"10.5897/jcbbr11.026","url":null,"abstract":"<p><p>The 21^st century emergence of genomic medicine is shifting the paradigm in biomedical science from the population phenotype to the individual genotype. In characterizing the biology of disease and health disparities in population genetics, human populations are often defined by the most common alleles in the group. This definition poses difficulties when categorizing individuals in the population who do not have the most common allele(s). Various epidemiological studies have shown an association between common genomic variation, such as single nucleotide polymorphisms (SNPs), and common diseases. We hypothesize that information encoded in the structure of SNP haploblock variation in the human leukocyte antigen-disease related (HLA-DR) region of the genome illumines molecular pathways and cellular mechanisms involved in the regulation of host adaptation to the environment. In this paper we describe the development and application of the normalized information content (NIC) as a novel metric based on SNP haploblock variation. The NIC facilitates translation of biochemical DNA sequence variation into a biophysical quantity derived from Boltzmann's canonical ensemble in statistical physics and used widely in information theory. Our normalization of this information metric allows for comparisons of unlike, or even unrelated, regions of the genome. We report here NIC values calculated for HLA-DR SNP haploblocks constructed by Haploview, a product of the International Haplotype Map Project. These haploblocks were scanned for potential regulatory elements using ConSite and miRBase, publicly available bioinformatics tools. We found that all of the haploblocks with statistically low NIC values contained putative transcription factor binding sites and microRNA motifs, suggesting correlation with genomic regulation. Thus, we were able to relate a mathematical measure of information content in HLA-DR SNP haploblocks to biologically relevant functional knowledge embedded in the structure of DNA sequence variation. We submit that NIC may be useful in analyzing the regulation of molecular pathways involved in host adaptation to environmental pathogens and in decoding the functional significance of common variation in the human genome.</p>","PeriodicalId":89969,"journal":{"name":"Journal of computational biology and bioinformatics research","volume":"4 2","pages":"15-22"},"PeriodicalIF":0.0,"publicationDate":"2012-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902476/pdf/nihms359905.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32075314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}