• 제목/요약/키워드: Computational biology

검색결과 204건 처리시간 0.027초

Efficient Mining of Interesting Patterns in Large Biological Sequences

  • Rashid, Md. Mamunur;Karim, Md. Rezaul;Jeong, Byeong-Soo;Choi, Ho-Jin
    • Genomics & Informatics
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    • 제10권1호
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    • pp.44-50
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    • 2012
  • Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

Predicting tissue-specific expressions based on sequence characteristics

  • Paik, Hyo-Jung;Ryu, Tae-Woo;Heo, Hyoung-Sam;Seo, Seung-Won;Lee, Do-Heon;Hur, Cheol-Goo
    • BMB Reports
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    • 제44권4호
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    • pp.250-255
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    • 2011
  • In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.

Bioinformatics in the Post-genome Era

  • Yu, Ung-Sik;Lee, Sung-Hoon;Kim, Young-Joo;Kim, Sang-Soo
    • BMB Reports
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    • 제37권1호
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    • pp.75-82
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    • 2004
  • Recent years saw a dramatic increase in genomic and proteomic data in public archives. Now with the complete genome sequences of human and other species in hand, detailed analyses of the genome sequences will undoubtedly improve our understanding of biological systems and at the same time require sophisticated bioinformatic tools. Here we review what computational challenges are ahead and what are the new exciting developments in this exciting field.

Revealing Regulatory Networks of DNA Repair Genes in S. Cerevisiae

  • Kim, Min-Sung;Lee, Do-Heon;Yi, Gwan-Su
    • Bioinformatics and Biosystems
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    • 제2권1호
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    • pp.12-16
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    • 2007
  • DNA repair means a collection of processes that a cell identifies and corrects damage to genome sequence. The DNA repair processes are important because a genome would not be able to maintain its essential cellular functions without the processes. In this research, we make some gene regulatory networks of DNA repair in S. cerevisiae to know how each gene interacts with others. Two approaches are adapted to make the networks; Bayesian Network and ARACNE. After construction of gene regulatory networks based on the two approaches, the two networks are compared to each other to predict which genes have important roles in the DNA repair processes by finding conserved interactions and looking for hubs. In addition, each interaction between genes in the networks is validated with interaction information in S. cerevisiae genome database to support the meaning of predicted interactions in the networks.

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Genome data mining for everyone

  • Lee, Gir-Won;Kim, Sang-Soo
    • BMB Reports
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    • 제41권11호
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    • pp.757-764
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    • 2008
  • The genomic sequences of a huge number of species have been determined. Typically, these genome sequences and the associated annotation data are accessed through Internet-based genome browsers that offer a user-friendly interface. Intelligent use of the data should expedite biological knowledge discovery. Such activity is collectively called data mining and involves queries that can be simple, complex, and even combinational. Various tools have been developed to make genome data mining available to computational and experimental biologists alike. In this mini-review, some tools that have proven successful will be introduced along with examples taken from published reports.

P2X Receptor 3D Structure Prediction Using Homology Modelling

  • Sruthy Sathish;Thirumurthy Madhavan
    • 통합자연과학논문집
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    • 제16권1호
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    • pp.39-45
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    • 2023
  • P2X receptors are ATP-activated ion channels in the plasma membrane. P2X receptors have a role in a diverse range of disorders, making them a valuable therapeutic target. Hence, the present investigation employed homology modelling of the P2X receptor based on the crystal structure of 5SVJ, 6AH4, 5YVE and 5SVL. Twenty models, using both single- and multiple template-based methods, were developed, and the best model was chosen based on the validation result. We observed that a strategy based on multiple templates provided greater accuracy. Future studies involving binding site and docking analysis can make use of the produced structures.

Systems Biology and Emerging Technologies Will Catalyze the Transition from Reactive Medicine to Predictive, Personalized, Preventive and Participatory (P4) Medicine

  • Galas, David J.;Hood, Leroy
    • Interdisciplinary Bio Central
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    • 제1권2호
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    • pp.6.1-6.4
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    • 2009
  • We stand at the brink of a fundamental change in how medicine will be practiced. Over the next 5-20 years medicine will move from being largely reactive to being predictive, personalized, preventive and participatory (P4). Technology and new scientific strategies have always been the drivers of revolutions and this is certainly the case for P4 medicine, where a systems approach to disease, new and emerging technologies and powerful computational tools will open new windows for the investigation of disease. Systems approaches are driving the emergence of fascinating new technologies that will permit billions of measurements on each individual patient. The challenge for health information technology will be how to reduce this enormous amount of data to simple hypotheses about health and disease. We predict that emerging technologies, together with the systems approaches to diagnosis, therapy and prevention will lead to a down turn in the escalating costs of healthcare. In time we will be able to export P4 medicine to the developing world and it will become the foundation of global medicine. The "democratization" of healthcare will come from P4 medicine. Its first real emergence will require the unprecedented integration of biology, medicine, technology and computation. as well as societal issues of major importance: ethical, regulatory, public policy, economic, and others. In order to effectively move the P4 scientific agenda forward new strategic partnerships are now being created with the large-scale integration of complementary skills, technologies, computational tools, patient records and samples and analysis of societal issues. It is evident that the business plans of every sector of the healthcare industry will need to be entirely transformed over the next 10 years.and the extent to which this will be done by existing companies as opposed to newly created companies is a fascinating question.

Habitat selectivity of fresh water fishes of two second-order tropical streams in Tigray, Northern Ethiopia

  • Tesfay, Solomon;Teferi, Mekonen;Tsegazeabe, Haileselasie Hadush
    • Journal of Ecology and Environment
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    • 제43권1호
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    • pp.73-83
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    • 2019
  • Background: Habitat selectivity and ecology of freshwater fishes were studied in two selected streams and their junction point which consist a total of 39 microhabitats. The aims of this study were to describe the habitat preference and its availability to fish assemblage, as well as ecology, habitat use, and habitat characteristics. Methods: We collected fish with backpack electrofishing three times during August 2013, December 2013, and March 2014. Using a variation partitioning approach of R software, we studied the relationship of fish abundances with stream type, habitat type, and abundance of key macroinvertebrate taxa. Results: A total of 6554 fishes representing four species belonging to the family Cyprinidae were caught. A higher total fish abundance was recorded from Gereb Tsedo (4870; 74.3%) than from Elala stream (1684; 25.7%). Taking both streams together, the overall total relative fish abundance was significantly higher in pools (53%) than in runs (35%) and in riffles (12%) at P < 0.05. Species-wise comparisons showed that 71%, 15%, 13%, and 1% of the pool fish community were occupied by Garra blanfordii, Garra ignestii, Garra dembecha, and Garra aethiopica, respectively. Stream type, habitat type, and key macroinvertebrate taxa each explained a significant proportion of the variation in fish abundance. Based on the variation partitioning approach, fish abundance was higher in Gereb Tsedo stream (P < 0.01). Moreover, fish abundance increased with pool habitat type (P < 0.01) and with availability of key macroinvertebrate taxa (P < 0.01). Conclusion: Fish abundance differed between stream types, among habitats and among key macroinvertebrate taxa availability. Among the factors, habitat type was the most important driving factor behind variation among fish abundances, and pool supports the highest fish abundance.

NONSELECTIVE HARVESTING OF A PEY-PREDATOR COMMUNITY WITH

  • Ghosh, Dipanwita;Sarkar, A.K.
    • Journal of applied mathematics & informatics
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    • 제6권3호
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    • pp.823-834
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    • 1999
  • The present paper deals with the problem of nonselective harvesting in a partly infecte prey and predator system in which both the suseptible prey and the predator follow the law of logistic growth and some preys avoid predation by hiding. The dynamical behaviour of the system has been studied in both the local and global sense. The optimal policy of exploitation has been derived by using Pontraygin's maximal principle. Numerical analysis and computer simulation of the results have been performed to inverstigate the global properties of the system.

Systems biology of virus-host signaling network interactions

  • Xue, Qiong;Miller-Jensen, Kathryn
    • BMB Reports
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    • 제45권4호
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    • pp.213-220
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    • 2012
  • Viruses have evolved to manipulate the host cell machinery for virus propagation, in part by interfering with the host cellular signaling network. Molecular studies of individual pathways have uncovered many viral host-protein targets; however, it is difficult to predict how viral perturbations will affect the signaling network as a whole. Systems biology approaches rely on multivariate, context-dependent measurements and computational analysis to elucidate how viral infection alters host cell signaling at a network level. Here we describe recent advances in systems analyses of signaling networks in both viral and non-viral biological contexts. These approaches have the potential to uncover virus- mediated changes to host signaling networks, suggest new therapeutic strategies, and assess how cell-to-cell variability affects host responses to infection. We argue that systems approaches will both improve understanding of how individual virus-host protein interactions fit into the progression of viral pathogenesis and help to identify novel therapeutic targets.