Displaying publications 221 - 240 of 340 in total

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  1. Fulltext Extracellular Vesicle-derived circular RNAs confers chemoresistance in Colorectal cancer
    Hon KW, Ab-Mutalib NS, Abdullah NMA, Jamal R, Abu N
    Sci Rep, 2019 Nov 11;9(1):16497.
    PMID: 31712601 DOI: 10.1038/s41598-019-53063-y
    Chemo-resistance is associated with poor prognosis in colorectal cancer (CRC), with the absence of early biomarker. Exosomes are microvesicles released by body cells for intercellular communication. Circular RNAs (circRNAs) are non-coding RNAs with covalently closed loops and enriched in exosomes. Crosstalk between circRNAs in exosomes and chemo-resistance in CRC remains unknown. This research aims to identify exosomal circRNAs associated with FOLFOX-resistance in CRC. FOLFOX-resistant HCT116 CRC cells (HCT116-R) were generated from parental HCT116 cells (HCT116-P) using periodic drug induction. Exosomes were characterized using transmission electron microscopy (TEM), Zetasizer and Western blot. Our exosomes were translucent cup-shaped structures under TEM with differential expression of TSG101, CD9, and CD63. We performed circRNAs microarray using exosomal RNAs from HCT116-R and HCT116-P cells. We validated our microarray data using serum samples. We performed drug sensitivity assay and cell cycle analysis to characterize selected circRNA after siRNA-knockdown. Using fold change >2 and p 
    Matched MeSH terms: Computational Biology/methods
  2. Fulltext A Fuzzy-C-Means-Clustering Approach: Quantifying Chromatin Pattern of Non-Neoplastic Cervical Squamous Cells
    Tang JR, Mat Isa NA, Ch'ng ES
    PLoS One, 2015;10(11):e0142830.
    PMID: 26560331 DOI: 10.1371/journal.pone.0142830
    Despite the effectiveness of Pap-smear test in reducing the mortality rate due to cervical cancer, the criteria of the reporting standard of the Pap-smear test are mostly qualitative in nature. This study addresses the issue on how to define the criteria in a more quantitative and definite term. A negative Pap-smear test result, i.e. negative for intraepithelial lesion or malignancy (NILM), is qualitatively defined to have evenly distributed, finely granular chromatin in the nuclei of cervical squamous cells. To quantify this chromatin pattern, this study employed Fuzzy C-Means clustering as the segmentation technique, enabling different degrees of chromatin segmentation to be performed on sample images of non-neoplastic squamous cells. From the simulation results, a model representing the chromatin distribution of non-neoplastic cervical squamous cell is constructed with the following quantitative characteristics: at the best representative sensitivity level 4 based on statistical analysis and human experts' feedbacks, a nucleus of non-neoplastic squamous cell has an average of 67 chromatins with a total area of 10.827 μm2; the average distance between the nearest chromatin pair is 0.508 μm and the average eccentricity of the chromatin is 0.47.
    Matched MeSH terms: Computational Biology/methods*
  3. Bioinformatics survey of the metal usage by psychrophilic yeast Glaciozyma antarctica PI12
    Foong PM, Abedi Karjiban R, Normi YM, Salleh AB, Abdul Rahman MB
    Metallomics, 2015 Jan;7(1):156-64.
    PMID: 25412156 DOI: 10.1039/c4mt00163j
    Metal ions are one of the essential elements which are extensively involved in many cellular activities. With rapid advancements in genome sequencing techniques, bioinformatics approaches have provided a promising way to extract functional information of a protein directly from its primary structure. Recent findings have suggested that the metal content of an organism can be predicted from its complete genome sequences. Characterizing the biological metal usage of cold-adapted organisms may help to outline a comprehensive understanding of the metal-partnerships between the psychrophile and its adjacent environment. The focus of this study is targeted towards the analysis of the metal composition of a psychrophilic yeast Glaciozyma antarctica PI12 isolated from sea ice of Antarctica. Since the cellular metal content of an organism is usually reflected in the expressed metal-binding proteins, the putative metal-binding sequences from G. antarctica PI12 were identified with respect to their sequence homologies, domain compositions, protein families and cellular distribution. Most of the analyses revealed that the proteome was enriched with zinc, and the content of metal decreased in the order of Zn > Fe > Mg > Mn, Ca > Cu. Upon comparison, it was found that the metal compositions among yeasts were almost identical. These observations suggested that G. antarctica PI12 could have inherited a conserved trend of metal usage similar to modern eukaryotes, despite its geographically isolated habitat.
    Matched MeSH terms: Computational Biology
  4. Functional features and protein network of human sperm-egg interaction
    Sabetian S, Shamsir MS, Abu Naser M
    Syst Biol Reprod Med, 2014 Dec;60(6):329-37.
    PMID: 25222562 DOI: 10.3109/19396368.2014.955896
    Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new computationally resolved interactions and the genetic links between sperm-egg interaction abnormalities and the associated disease.
    Matched MeSH terms: Computational Biology
  5. Fulltext Sequence analysis of the PIP5K locus in Eimeria maxima provides further evidence for eimerian genome plasticity and segmental organization
    Song BK, Pan MZ, Lau YL, Wan KL
    Genet. Mol. Res., 2014;13(3):5803-14.
    PMID: 25117339 DOI: 10.4238/2014.July.29.8
    Commercial flocks infected by Eimeria species parasites, including Eimeria maxima, have an increased risk of developing clinical or subclinical coccidiosis; an intestinal enteritis associated with increased mortality rates in poultry. Currently, infection control is largely based on chemotherapy or live vaccines; however, drug resistance is common and vaccines are relatively expensive. The development of new cost-effective intervention measures will benefit from unraveling the complex genetic mechanisms that underlie host-parasite interactions, including the identification and characterization of genes encoding proteins such as phosphatidylinositol 4-phosphate 5-kinase (PIP5K). We previously identified a PIP5K coding sequence within the E. maxima genome. In this study, we analyzed two bacterial artificial chromosome clones presenting a ~145-kb E. maxima (Weybridge strain) genomic region spanning the PIP5K gene locus. Sequence analysis revealed that ~95% of the simple sequence repeats detected were located within regions comparable to the previously described feature-rich segments of the Eimeria tenella genome. Comparative sequence analysis with the orthologous E. maxima (Houghton strain) region revealed a moderate level of conserved synteny. Unique segmental organizations and telomere-like repeats were also observed in both genomes. A number of incomplete transposable elements were detected and further scrutiny of these elements in both orthologous segments revealed interesting nesting events, which may play a role in facilitating genome plasticity in E. maxima. The current analysis provides more detailed information about the genome organization of E. maxima and may help to reveal genotypic differences that are important for expression of traits related to pathogenicity and virulence.
    Matched MeSH terms: Computational Biology
  6. Fulltext Endogenous lentivirus in Malayan colugo (Galeopterus variegatus), a close relative of primates
    Hron T, Fábryová H, Pačes J, Elleder D
    Retrovirology, 2014;11:84.
    PMID: 25280529 DOI: 10.1186/s12977-014-0084-x
    A significant fraction of mammalian genomes is composed of endogenous retroviral (ERV) sequences that are formed by germline infiltration of various retroviruses. In contrast to other retroviral genera, lentiviruses only rarely form ERV copies. We performed a computational search aimed at identification of novel endogenous lentiviruses in vertebrate genomes.
    Matched MeSH terms: Computational Biology
  7. Fulltext A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology
    Koo CL, Liew MJ, Mohamad MS, Salleh AH
    Biomed Res Int, 2013;2013:432375.
    PMID: 24228248 DOI: 10.1155/2013/432375
    Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
    Matched MeSH terms: Computational Biology
  8. Fulltext Comparative analysis of Mafriwal (Bos taurus × Bos indicus) and Kedah Kelantan (Bos indicus) sperm proteome identifies sperm proteins potentially responsible for higher fertility in a tropical climate
    Ashrafzadeh A, Nathan S, Karsani SA
    Int J Mol Sci, 2013;14(8):15860-77.
    PMID: 23903046 DOI: 10.3390/ijms140815860
    The fertility of zebu cattle (Bos indicus) is higher than that of the European purebred (Bos taurus) and crossbred (Bos taurus × Bos indicus) cattle in tropical areas. To identify proteins related to the higher thermo-tolerance and fertility of Zebu cattle, this study was undertaken to identify differences in sperm proteome between the high fertile Malaysian indigenous zebu cattle (Kedah Kelantan) and the sub-fertile crossbred cattle (Mafriwal). Frozen semen from three high performance bulls from each breed were processed to obtain live and pure sperm. Sperm proteins were then extracted, and two-dimensional gel electrophoresis performed to compare proteome profiles. Gel image analysis identified protein spots of interest which were then identified by liquid chromatography mass spectrometry quadrupole time-of-flight (LC MS/MS Q-TOF). STRING network analysis predicted interactions between at least 20 of the identified proteins. Among the identified proteins, a number of motility and energy related proteins were present in greater abundance in Kedah Kelantan. Sperm motility evaluation by Computer Assisted Semen Analysis (CASA) confirmed significantly higher motility in Kedah Kelantan. While results from this study do identify proteins that may be responsible for the higher fertility of Kedah Kelantan, functional characterization of these proteins is warranted to reinforce our understanding of their roles in sperm fertility.
    Matched MeSH terms: Computational Biology
  9. Fulltext Gene expression changes associated with the airway wall response to injury
    Yahaya B, McLachlan G, McCorquodale C, Collie D
    PLoS One, 2013;8(4):e58930.
    PMID: 23593124 DOI: 10.1371/journal.pone.0058930
    BACKGROUND: Understanding the way in which the airway heals in response to injury is fundamental to dissecting the mechanisms underlying airway disease pathology. As only limited data is available in relation to the in vivo characterisation of the molecular features of repair in the airway we sought to characterise the dynamic changes in gene expression that are associated with the early response to physical injury in the airway wall.

    METHODOLOGY/PRINCIPAL FINDINGS: We profiled gene expression changes in the airway wall using a large animal model of physical injury comprising bronchial brush biopsy in anaesthetised sheep. The experimental design featured sequential studies in the same animals over the course of a week and yielded data relating to the response at 6 hours, and 1, 3 and 7 days after injury. Notable features of the transcriptional response included the early and sustained preponderance of down-regulated genes associated with angiogenesis and immune cell activation, selection and differentiation. Later features of the response included the up-regulation of cell cycle genes at d1 and d3, and the latter pronounced up-regulation of extracellular matrix-related genes at d3 and d7.

    CONCLUSIONS/SIGNIFICANCE: It is possible to follow the airway wall response to physical injury in the same animal over the course of time. Transcriptional changes featured coordinate expression of functionally related genes in a reproducible manner both within and between animals. This characterisation will provide a foundation against which to assess the perturbations that accompany airway disease pathologies of comparative relevance.

    Matched MeSH terms: Computational Biology
  10. Performance of univariate forecasting on seasonal diseases: the case of tuberculosis
    Permanasari AE, Rambli DR, Dominic PD
    Adv Exp Med Biol, 2011;696:171-9.
    PMID: 21431557 DOI: 10.1007/978-1-4419-7046-6_17
    The annual disease incident worldwide is desirable to be predicted for taking appropriate policy to prevent disease outbreak. This chapter considers the performance of different forecasting method to predict the future number of disease incidence, especially for seasonal disease. Six forecasting methods, namely linear regression, moving average, decomposition, Holt-Winter's, ARIMA, and artificial neural network (ANN), were used for disease forecasting on tuberculosis monthly data. The model derived met the requirement of time series with seasonality pattern and downward trend. The forecasting performance was compared using similar error measure in the base of the last 5 years forecast result. The findings indicate that ARIMA model was the most appropriate model since it obtained the less relatively error than the other model.
    Matched MeSH terms: Computational Biology
  11. Asynchronous brain machine interface-based control of a wheelchair
    Hema CR, Paulraj MP, Yaacob S, Adom AH, Nagarajan R
    Adv Exp Med Biol, 2011;696:565-72.
    PMID: 21431597 DOI: 10.1007/978-1-4419-7046-6_57
    A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the classification of the four mental states. The real-time experiment results of four subjects are reported and problems emerging from asynchronous control are discussed.
    Matched MeSH terms: Computational Biology
  12. A study on discrete wavelet-based noise removal from EEG signals
    Asaduzzaman K, Reaz MB, Mohd-Yasin F, Sim KS, Hussain MS
    Adv Exp Med Biol, 2010;680:593-9.
    PMID: 20865544 DOI: 10.1007/978-1-4419-5913-3_65
    Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.
    Matched MeSH terms: Computational Biology
  13. An MLP neural network for ECG noise removal based on Kalman filter
    Moein S
    Adv Exp Med Biol, 2010;680:109-16.
    PMID: 20865492 DOI: 10.1007/978-1-4419-5913-3_13
    In this paper, application of Artificial Neural Network (ANN) for electrocardiogram (ECG) signal noise removal has been investigated. First, 100 number of ECG signals are selected from Physikalisch-Technische Bundesanstalt (PTB) database and Kalman filter is applied to remove their low pass noise. Then a suitable dataset based on denoised ECG signal is configured and used to a Multilayer Perceptron (MLP) neural network to be trained. Finally, results and experiences are discussed and the effect of changing different parameters for MLP training is shown.
    Matched MeSH terms: Computational Biology
  14. Genome-wide prediction and annotation of Burkholderia pseudomallei AraC/XylS family transcription regulator
    Lim BS, Chong CE, Zamrod Z, Nathan S, Mohamed R
    In Silico Biol. (Gedrukt), 2007;7(4-5):389-97.
    PMID: 18391231
    Many members of the AraC/XylS family transcription regulator have been proven to play a critical role in regulating bacterial virulence factors in response to environmental stress. By using the Hidden Markov Model (HMM) profile built from the alignment of a 99 amino acid conserved domain sequence of 273 AraC/XylS family transcription regulators, we detected a total of 45 AraC/XylS family transcription regulators in the genome of the Gram-negative pathogen, Burkholderia pseudomallei. Further in silico analysis of each detected AraC/XylS family transcription regulatory protein and its neighboring genes allowed us to make a first-order guess on the role of some of these transcription regulators in regulating important virulence factors such as those involved in three type III secretion systems and biosynthesis of pyochelin, exopolysaccharide (EPS) and phospholipase C. This paper has demonstrated an efficient and systematic genome-wide scale prediction of the AraC/XylS family that can be applied to other protein families.
    Matched MeSH terms: Computational Biology
  15. In silico analysis of Burkholderia pseudomallei genome sequence for potential drug targets
    Chong CE, Lim BS, Nathan S, Mohamed R
    In Silico Biol. (Gedrukt), 2006;6(4):341-6.
    PMID: 16922696
    Recent advances in DNA sequencing technology have enabled elucidation of whole genome information from a plethora of organisms. In parallel with this technology, various bioinformatics tools have driven the comparative analysis of the genome sequences between species and within isolates. While drawing meaningful conclusions from a large amount of raw material, computer-aided identification of suitable targets for further experimental analysis and characterization, has also led to the prediction of non-human homologous essential genes in bacteria as promising candidates for novel drug discovery. Here, we present a comparative genomic analysis to identify essential genes in Burkholderia pseudomallei. Our in silico prediction has identified 312 essential genes which could also be potential drug candidates. These genes encode essential proteins to support the survival of B. pseudomallei including outer-inner membrane and surface structures, regulators, proteins involved in pathogenenicity, adaptation, chaperones as well as degradation of small and macromolecules, energy metabolism, information transfer, central/intermediate/miscellaneous metabolism pathways and some conserved hypothetical proteins of unknown function. Therefore, our in silico approach has enabled rapid screening and identification of potential drug targets for further characterization in the laboratory.
    Matched MeSH terms: Computational Biology
  16. Fulltext Development of high-throughput SNP-based genotyping in Acacia auriculiformis x A. mangium hybrids using short-read transcriptome data
    Wong MM, Cannon CH, Wickneswari R
    BMC Genomics, 2012;13:726.
    PMID: 23265623 DOI: 10.1186/1471-2164-13-726
    Next Generation Sequencing has provided comprehensive, affordable and high-throughput DNA sequences for Single Nucleotide Polymorphism (SNP) discovery in Acacia auriculiformis and Acacia mangium. Like other non-model species, SNP detection and genotyping in Acacia are challenging due to lack of genome sequences. The main objective of this study is to develop the first high-throughput SNP genotyping assay for linkage map construction of A. auriculiformis x A. mangium hybrids.
    Matched MeSH terms: Computational Biology
  17. Fulltext Computational discovery and RT-PCR validation of novel Burkholderia conserved and Burkholderia pseudomallei unique sRNAs
    Khoo JS, Chai SF, Mohamed R, Nathan S, Firdaus-Raih M
    BMC Genomics, 2012;13 Suppl 7:S13.
    PMID: 23282220 DOI: 10.1186/1471-2164-13-S7-S13
    The sRNAs of bacterial pathogens are known to be involved in various cellular roles including environmental adaptation as well as regulation of virulence and pathogenicity. It is expected that sRNAs may also have similar functions for Burkholderia pseudomallei, a soil bacterium that can adapt to diverse environmental conditions, which causes the disease melioidosis and is also able to infect a wide variety of hosts.
    Matched MeSH terms: Computational Biology
  18. Comparative analysis of viral genomes from acute and chronic hepatitis B reveals novel variants associated with a lower rate of chronicity
    Chook JB, Ngeow YF, Khang TF, Ng KP, Tiang YP, Mohamed R
    J Med Virol, 2013 Mar;85(3):419-24.
    PMID: 23297244 DOI: 10.1002/jmv.23500
    Infection with the hepatitis B virus (HBV) may lead to an acute or chronic infection. It is generally accepted that the clinical outcome of infection depends on the balance between host immunity and viral survival strategies. In order to persist, the virus needs to have a high rate of replication and some immune-escape capabilities. Hence, HBVs lacking these properties are likely to be eliminated more rapidly by the host, leading to a lower rate of chronicity. To test this hypothesis, 177 HBV genomes from acute non-fulminant cases and 1,149 from chronic cases were retrieved from GenBank for comparative analysis. Selection of candidate nucleotides associated with the disease state was done using random guess cut-off and the Bonferroni correction. Five significant nucleotides were detected using this filtering step. Their predictive values were assessed using the support vector machine classification with five-fold cross-validation. The average prediction accuracy was 61% ± 1%, with a sensitivity of 24% ± 1%, specificity of 98% ± 1%, positive predictive value of 92% ± 4% and negative predictive value of 56% ± 1%. BCP/X, enhancer I and surface/polymerase variants were found to be associated almost exclusively with acute hepatitis. These HBV variants are novel potential markers for non-progression to chronic hepatitis.
    Matched MeSH terms: Computational Biology
  19. Granulometric analysis of spots in DNA microarray images
    Latha B, Venkatesh B
    Genomics Proteomics Bioinformatics, 2004 Nov;2(4):222-36.
    PMID: 15901251
    As the topological properties of each spot in DNA microarray images may vary from one another, we employed granulometries to understand the shape-size content contributed due to a significant intensity value within a spot. Analysis was performed on the microarray image that consisted of 240 spots by using concepts from mathematical morphology. In order to find out indices for each spot and to further classify them, we adopted morphological multiscale openings, which provided microarrays at multiple scales. Successive opened microarrays were subtracted to identify the protrusions that were smaller than the size of structuring element. Spot-wise details, in terms of probability of these observed protrusions, were computed by placing a regularly spaced grid on microarray such that each spot was centered in each grid. Based on the probability of size distribution functions of these protrusions isolated at each level, we estimated the mean size and texture index for each spot. With these characteristics, we classified the spots in a microarray image into bright and dull categories through pattern spectrum and shape-size complexity measures. These segregated spots can be compared with those of hybridization levels.
    Matched MeSH terms: Computational Biology
  20. Fulltext Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA
    Namazi H, Kiminezhadmalaie M
    Comput Math Methods Med, 2015;2015:242695.
    PMID: 26539245 DOI: 10.1155/2015/242695
    Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers.
    Matched MeSH terms: Computational Biology
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