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Interdisciplinary Sciences, Computational Life Sciences

Mouna Choura, Ahmed Rebaï
Intrinsically disordered proteins (IDPs) are often involved in diseases and have been shown to be promising targets for drug development. Here, we focus on the human disordered charged biased proteins (HDCBPs). We have investigated the association of the HDCBPs with diseases by integrating various sources that cover public sources of gene-disease associations and intensive literature mining. The results indicate that 95% of HDCBPs are associated with multiple diseases, including mainly various cancers, nervous, endocrine, immune, hematological, and respiratory systems diseases...
January 11, 2019: Interdisciplinary Sciences, Computational Life Sciences
Bo Hu, Xiao Chang, Xiaoping Liu
Complex diseases are generally caused by disorders of biological networks or/and mutations in multiple genes. The efficient and systematic identification of functional modules can not only supply effective diagnosis and treatment in clinic, but also benefit in further in-depth analysis of the pathological mechanism of complex diseases. In this study, we applied the method of differential network to identify functional modules between control and disease samples, which are different from most of the current approaches that focus on differential expression...
January 2, 2019: Interdisciplinary Sciences, Computational Life Sciences
Amani Al-Ajlan, Achraf El Allali
Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs are based on extracting a large number of features and then applying statistical approaches or supervised classification approaches to predict genes. In our study, we introduce a convolutional neural network for metagenomics gene prediction (CNN-MGP) program that predicts genes in metagenomics fragments directly from raw DNA sequences, without the need for manual feature extraction and feature selection stages...
December 27, 2018: Interdisciplinary Sciences, Computational Life Sciences
Kaja Gutowska, Dorota Formanowicz, Piotr Formanowicz
Many factors, such as endothelial dysfunction, inflammation and hemostatic disturbances, affect formation and progression of atherosclerotic plaque. In our study, we have focused on hemostatic disturbances with particular emphasis on the extrinsic pathways of coagulation. Thrombin is a main enzyme of coagulation and it is engaged in many different subprocesses. It leads to activation of factors of the coagulation cascade, transition of fibrinogen to fibrin monomer, endothelial damage, inflammation, activation of platelets and proliferation...
December 24, 2018: Interdisciplinary Sciences, Computational Life Sciences
Lina Teresa Gaudio, Pierangelo Veltri, Salvatore De Rosa, Ciro Indolfi, Gionata Fragomeni
Cardiovascular diseases are among the main causes of morbidity, disability, and mortality. Most of them occur because of an atherosclerotic plaque developing within a coronary artery, which can cause a narrowing of the vessel lumen (coronary stenosis) or even break it. It is, therefore, useful to evaluate the role of the stress state of the endothelial layer of the arterial tissue, both for the maintenance of the blood circulation and for the implications in presence of a pathology that can lead to thromboembolic complications...
December 7, 2018: Interdisciplinary Sciences, Computational Life Sciences
Hugo López-Fernández, Pedro Duque, Sílvia Henriques, Noé Vázquez, Florentino Fdez-Riverola, Cristina P Vieira, Miguel Reboiro-Jato, Jorge Vieira
Useful insight into the evolution of genes and gene families can be provided by the analysis of all available genome datasets rather than just a few, which are usually those of model species. Handling and transforming such datasets into the desired format for downstream analyses is, however, often a difficult and time-consuming task for researchers without a background in informatics. Therefore, we present two simple and fast protocols for data preparation, using an easy-to-install, open-source, cross-platform software application with user-friendly, rich graphical user interface (SEDA; http://www...
December 3, 2018: Interdisciplinary Sciences, Computational Life Sciences
Muhammad Ibrahim Rashid, Amjad Ali, Saadia Andleeb
Dual Oxidase 1 (DUOX1) is a prominent immune system component primarily expressed in esophagus, lungs, skin, and urinary bladder including others. DUOX1 is involved in lactoperoxidase-mediated innate immunity at mucosal surfaces by generation of antimicrobial hypothiocyanite at the apical surface of epithelial lining. Upon detection of bacterial pathogens mainly Pseudomonas aeruginosa, DUOX1 is activated in bronchial epithelial cells. Both the host and pathogen enter a redox dual with DUOX1 and hypothiocyanite from host and Pyocyanin (PCN) as a redox active virulence factor from P...
November 27, 2018: Interdisciplinary Sciences, Computational Life Sciences
Sh Hashemzadeh, F Ramezani, H Rafii-Tabar
Trametinib was endorsed by the FDA in 2013 as a single agent for adult melanoma patients. Trametinib inhibits cell growth and proliferation in multiple tumor xenografts by preventing RAF phosphorylation of MEK and thus restricting accumulation of activated MEK. In this study, the focus of investigation was the mechanism of the interaction between trametinib and MEK1/2 via computational simulation. To specify the best interaction site of inhibitor with MEK1/2 based on the interaction energy ranking, first we performed a docking and then we studied the interactions of the ATP-bound MEK with trametinib, with RAF and the complex of the ATP-bound MEK-trametinib with RAF via molecular dynamic simulations...
November 21, 2018: Interdisciplinary Sciences, Computational Life Sciences
Divya Khanna, Prashant Singh Rana
Development of an effective machine-learning model for T-cell Mycobacterium tuberculosis (M. tuberculosis) epitopes is beneficial for saving biologist's time and effort for identifying epitope in a targeted antigen. Existing NetMHC 2.2, NetMHC 2.3, NetMHC 3.0 and NetMHC 4.0 estimate binding capacity of peptide. This is still a challenge for those servers to predict whether a given peptide is M. tuberculosis epitope or non-epitope. One of the servers, CTLpred, works in this category but it is limited to peptide length of 9-mers...
November 7, 2018: Interdisciplinary Sciences, Computational Life Sciences
Dhiraj Kumar, Pravir Kumar
Malicious progression of neurodegeneration is a consequence of toxic aggregates of proteins or peptides such as amyloid beta (Aβ) reported in Alzheimer's disease (AD). These aggregates hinder the electrochemical transmission at neuronal junctions and thus deteriorate neuronal-health by triggering dementia. Electrostatic and hydrophobic interactions among amino-acid residues are the governing principle behind the self-assembly of aforesaid noxious oligomers or agglomerate. Interestingly, lysine residues are crucial for these interactions and for facilitating the clearance of toxic metabolites through the ubiquitination process...
September 7, 2018: Interdisciplinary Sciences, Computational Life Sciences
Beili Ying, Shichao Pang, Junchen Yang, Yang Zhong, Jingfang Wang
HCV p7 protein is a cation-selective ion channel, playing an essential role during the life cycle of HCV viruses. To understand the cation-selective mechanism, we constructed a hexameric model in lipid bilayers of HCV p7 protein for HCB JFH-1 strain, genotype 2a. In this structural model, His9 and Val6 were key factors for the HCV cation-selective ion channel. The histidine residues at position 9 in the hexameric model formed a first gate for HCV p7 channel, acting as a selectivity filter for cations. The valines mentioned above formed a second gate for HCV p7 channel, serving as a hydrophobic filter for the dehydrated cations...
September 7, 2018: Interdisciplinary Sciences, Computational Life Sciences
G Pavithrra, R Rajasekaran
Discovering and developing the antimicrobial peptides are recently focused on pharmaceutical firm, since they serve as complementary to antibiotics in prevailing over drug resistance by eliciting the disruption of microbial membrane. Still, there are lots of challenges to bring up the structurally stable and functionally efficient antimicrobial peptides. It is well known that gramicidin D is the prominent antimicrobial peptide that exists as g-AB, g-BC, and g-AC. This study analyzes the structural stability and the functional activity of hetero-dimeric double-stranded gramicidin-D peptides, thereby demonstrating its potent antimicrobial activity against antibiotic-resistant micro-organisms...
September 4, 2018: Interdisciplinary Sciences, Computational Life Sciences
Hanshu Cai, Yunfei Chen, Jiashuo Han, Xiangzi Zhang, Bin Hu
The early diagnosis of depression is important to the treatment of this condition, whereas a timely diagnosis can reduce the incidence of mortality caused in patients with depression. In the present study, we collected the EEG signals of Fp2, Fpz and Fp1, compared with 128 channels EEG, a simpler test (3 channels EEG) can make diagnosis more accessible and widespread, researchers can perform more tests on more patients given the same amount of time and money. The difference between the depressed and the non-depressed patients was explored by the linear and non-linear characteristics of these EEG signals...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Yaogong Zhang, Jiahui Liu, Xiaohu Liu, Yuxiang Hong, Xin Fan, Yalou Huang, Yuan Wang, Maoqiang Xie
Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Chittabrata Mal, Md Aftabuddin, Sudip Kundu
BACKGROUND: Growing evidences suggest that microRNAs (miRNAs) can efficiently regulate gene expression at intracellular and extracellular levels. It has been previously reported that plant/food-derived miRNAs are highly enriched in human serum or serum from phytophagous animals, and they are responsible for regulating mammalian gene expression. Thus, miRNAs could function as active signaling molecules, which carry information across distinct species or even kingdoms. However, the mode of miRNA shuttling among various organisms is still a mystery to unravel...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Mingming Zhang, Hongbo Mu, Ruijie Zhang, Shenkui Liu, Imshik Lee
Salt stress is a common abiotic stress in agricultural production, which is affected by multiple genes and environmental factors. Although transcriptome analyses have detected some salt-related genes in Arabidopsis thaliana, these genes are often major genes and can not adequately explain the molecular mechanism of salt tolerance. Some genes related to salt stress, but does not reach significant threshold in gene expression analysis (called modest effect genes), are often ignored. Therefore, we took full account of the role of modest effect genes and performed a pathway-based analysis of three gene microarray datasets to identify the pathways related to salt stress...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Lijun Tang, Nan Zhou
Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Patrizia Vizza, Giuseppe Tradigo, Pietro Hiram Guzzi, Rosario Curia, Loredana Sisca, Filippo Aiello, Gionata Fragomeni, Mario Cannataro, Giuseppe Lucio Cascini, Pierangelo Veltri
The collection and analysis of clinical data are needed to investigate diseases and to define medical protocols and treatments. Bioimages, medical annotations and patient history are clinical data acquired and studied to perform a correct diagnosis and to propose an appropriate therapy. Currently, hospital departments manage these data using legacy systems which do not often allow data integration among different departments or health structures. Thus, in many cases clinical information sharing and exchange are difficult to implement...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Anjana Rajendiran, Aniruddha Chatterjee, Archana Pan
MicroRNAs (miRNAs) are a family of non-coding RNAs that play a central role in fine-tuning gene expression regulation. Over the past decade, identification and annotation of miRNAs have become a major focus in epigenomics research. However, detection and characterization of miRNA are challenging due to its small size (~22 nucleotide-long) and susceptibility to degradation. The difficulties involved in experimental prediction and characterization of miRNA coding genes have led to the development of in silico-based approaches...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
Anvita Gupta Malhotra, Mohit Jha, Sudha Singh, Khushhali M Pandey
Vitiligo is an idiopathic disorder characterized by depigmented patches on the skin due to progressive loss of melanocytes. Several genetic, immunological, and pathophysiological investigations have established vitiligo as a polygenetic disorder with multifactorial etiology. However, no definite model explaining the interplay between these causative factors has been established hitherto. Therefore, we studied the disorder at the system level to identify the key proteins involved by exploring their molecular connectivity in terms of topological parameters...
September 2018: Interdisciplinary Sciences, Computational Life Sciences
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