Papers by Dr Mohammad Ali Moni
Briefings in Bioinformatics, 2020
The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significan... more The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA-DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein-chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P...
European Journal of Medical and Health Sciences
This study compared different detection methods of human/simian immunodeficiency virus (HIV/SIV) ... more This study compared different detection methods of human/simian immunodeficiency virus (HIV/SIV) infections in the cell line systems; notably, i) Indirect immunofluorescence assay (IFA), ii) integrated proviral DNA detection, iii) detection of syncytia, iv) measurement of reverse transcriptase (RT) activity. RTs of various retroviruses require cations, including Mg2+, Mn2+, Ni2+, and Cu2+, for their enzyme-activities. The study further compared the roles of Mg2+ and Mn2+ as cofactors for RT activities of freshly harvested HIV-1, HIV-2, and SIV. The NP-2/CD4/coreceptor cells were seeded for overnight and infected with viral inoculums at a multiplicity of infection (MOI) 1.0. The cells were passaged regularly in a 2-3 days interval and maintained up to 2 weeks. Infected cells were detected by indirect immunofluorescence assay (IFA). Multinucleated giant cells (MGC) in syncytia were quantified by Giemsa-staining. Proviral DNA was detected by PCR, and reverse transcriptase (RT) activit...
Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach
Genomics
Onset, Transmission, Impact, and Management of COVID-19 Epidemic at Early Stage in SAARC Countries
Identification of the core ontologies and signature genes of polycystic ovary syndrome (PCOS): A bioinformatics analysis
Informatics in Medicine Unlocked
RNA interference (RNAi) plays key roles in post-transcriptional and chromatin modification levels... more RNA interference (RNAi) plays key roles in post-transcriptional and chromatin modification levels as well as regulates various eukaryotic gene expressions which involved in stress responses, development and maintenance of genome integrity during developmental stages. The whole mechanism of RNAi pathway is directly involved with the gene-silencing process by the interaction of Dicer-Like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) gene families. However, the genes of these three RNAi families are largely unknown yet in sweet orange (Citrus sinensis), though it is an economically important fruit plant all over the world. Therefore, a comprehensive investigation for genome-wide identification, characterization and diversity analysis of RNA silencing genes in C. sinensis was conducted and identified 4 CsDCL, 8 CsAGO and 4 CsRDR as RNAi genes. To characterize and validate the predicted genes of RNAi families, various bioinformatics analysis was conducted. Phylogenetic a...
IEEE Access
Type 2 diabetes (T2D) is a chronic metabolic disorder characterised by high blood sugar and insul... more Type 2 diabetes (T2D) is a chronic metabolic disorder characterised by high blood sugar and insulin insensitivity which greatly increases the risk of developing neurological diseases (NDs). The coexistence of T2D and comorbidities such as NDs can complicate or even cause the failure of standard treatments for those diseases. Comorbidities can be both causally linked and influence each other's development through genetic, molecular, environmental or lifestyle-based risk factors that they share. For T2D and NDs, such underlying common molecular mechanisms remain elusive but large amounts of molecular data accumulated on these diseases enable analytical approaches to identify their interconnected pathways. Here, we propose a framework to explore possible comorbidity interactions between a pair of diseases using a bioinformatic examination of the cellular pathways involved and explore this framework for T2D and NDs with analyses of a large number of publicly available gene expression datasets from tissues affected by these diseases. We designed a bioinformatics pipeline to analyse, utilize and combine gene expression, Gene Ontology (GO) and molecular pathway data by incorporating Gene Set Enrichment Analysis and Semantic Similarity. Our bioinformatics methodology was implemented in R, available at https://github.com/HabibUCAS/T2D_Comorbidity. We identified genes with altered expression shared by T2D and NDs as well as GOs and molecular pathways these diseases share. We also computed the proximity between T2D and neurological pathologies using these genes and GO term semantic similarity. Thus, our method has generated new insights into disease mechanisms important for both T2D and NDs that may mediate their interaction. Our bioinformatics pipeline could be applied to other co-morbidities to identify possible interactions and causal relationships between them.
IET Systems Biology
Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function... more Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function. The mechanisms underlying CMP development are poorly understood, but lifestyle factors are clearly implicated as risk factors. This study aimed to identify molecular biomarkers involved in inflammatory CMP development and progression using a systems biology approach. The authors analysed microarray gene expression datasets from CMP and tissues affected by risk factors including smoking, ageing factors, high body fat, clinical depression status, insulin resistance, high dietary red meat intake, chronic alcohol consumption, obesity, high-calorie diet and high-fat diet. The authors identified differentially expressed genes (DEGs) from each dataset and compared those from CMP and risk factor datasets to identify common DEGs. Gene set enrichment analyses identified metabolic and signalling pathways, including MAPK, RAS signalling and cardiomyopathy pathways. Protein-protein interaction (PPI) network analysis identified protein subnetworks and ten hub proteins (CDK2, ATM, CDT1, NCOR2, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D, HIST1H4E and HIST1H4L). Five transcription factors (FOXC1, GATA2, FOXL1, YY1, CREB1) and five miRNAs were also identified in CMP. Thus the authors' approach reveals candidate biomarkers that may enhance understanding of mechanisms underlying CMP and their link to risk factors. Such biomarkers may also be useful to develop new therapeutics for CMP.
A computational approach to identify blood cell-expressed Parkinson's disease biomarkers that are coordinately expressed in brain tissue
Computers in Biology and Medicine
Identification of genes whose regulation of expression is functionally similar in both brain tiss... more Identification of genes whose regulation of expression is functionally similar in both brain tissue and blood cells could in principle enable monitoring of significant neurological traits and disorders by analysis of blood samples. We thus employed transcriptional analysis of pathologically affected tissues, using agnostic approaches to identify overlapping gene functions and integrating this transcriptomic information with expression quantitative trait loci (eQTL) data. Here, we estimate the correlation of gene expression in the top-associated cis-eQTLs of brain tissue and blood cells in Parkinson's Disease (PD). We introduced quantitative frameworks to reveal the complex relationship of various biasing genetic factors in PD, a neurodegenerative disease. We examined gene expression microarray and RNA-Seq datasets from human brain and blood tissues from PD-affected and control individuals. Differentially expressed genes (DEG) were identified for both brain and blood cells to determine common DEG overlaps. Based on neighborhood-based bench-marking and multilayer network topology approaches we then developed genetic associations of factors with PD. Overlapping DEG sets underwent gene enrichment using pathway analysis and gene ontology methods, which identified candidate common genes and pathways. We identified 12 significantly dysregulated genes shared by brain and blood cells, which were validated using dbGaP (gene SNP-disease linkage) database for gold-standard benchmarking of their significance in disease processes. Ontological and pathway analyses identified significant gene ontology and molecular pathways that indicate PD progression. In sum, we found possible novel links between pathological processes in brain tissue and blood cells by examining cell pathway commonalities, corroborating these associations using well validated datasets. This demonstrates that for brain-related pathologies combining gene 1 expression analysis and blood cell cis-eQTL is a potentially powerful analytical approach. Thus, our methodologies facilitate data-driven approaches that can advance knowledge of disease mechanisms and may, with clinical validation, enable prediction of neurological dys-function using blood cell transcript profiling.
Detection of Multiple Sclerosis using Blood and Brain Cells Transcript Profiles: Insights from Comprehensive Bioinformatics Approach
Informatics in Medicine Unlocked
Early Detection of Autism by Extracting Features: A Case Study in Bangladesh
2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)
ABSTRACTPlatinum drugs cisplatin and carboplatin, given in combination with paclitaxel, constitut... more ABSTRACTPlatinum drugs cisplatin and carboplatin, given in combination with paclitaxel, constitute the standard chemotherapy against ovarian cancer (OC). Oc chemoresistance is a major obstacle to effective treatment, but knowledge of the mechanisms that underlie it remains incomplete. We thus sought to discover key proteins associated with platinum resistance by comparing A2780 OC cells with A2780cisR cells (resistant cells derived from the A2780 line) to identify proteins with markedly altered expression levels in the resistant cells. We also determined which proteins in these cells had altered expression in response to treatment with either designed monofunctional platinum alone or a combination with cisplatin with selected phytochemical therapeutic agents.We thus performed proteomic analysis using 2D-gel electrophoresis A2780 and A2780cisR to identify proteins with differential expression; these were eluted and analysed by mass spectrometry to identify them. A total of 122 protei...
Genetic effects of welding fumes on the development of respiratory system diseases
Computers in Biology and Medicine
Background and objectives: Colorectal cancer (CRC) is the 2nd most cause of cancer related death ... more Background and objectives: Colorectal cancer (CRC) is the 2nd most cause of cancer related death in the world, but early diagnosis ameliorates the survival of CRC. This report directed to identify molecular biomarker signatures in CRC. Materials and Methods: We analyzed two microarray datasets (GSE35279 and GSE21815) to identify common differentially expressed genes (DEGs). We performed functional overrepresentation, pathway enrichment, protein-protein interaction (PPI), reporter biomolecules, survival, and drug repositioning analyses were done on common DEGs. Results: Total 727 up-regulated and 99 down-regulated DEGs were detected. The significantly enriched pathways PI3K-Akt signaling, Wnt signaling, ECM-interaction, cell cycles were identified. The 10 hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2) were selected as proteomic signatures from PPI network. Analyses revealed 10 reporter transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1...
Background: Welding exposes a lot of gases, fumes and radiant energy that may be potentially haza... more Background: Welding exposes a lot of gases, fumes and radiant energy that may be potentially hazardous for unsafe welder's health. Welding fumes (WFs) are a severe problem among all those exposed. WFs are an intricate composition of metallic oxides, fluorides and silicates that may effect to the progression of various health problems. If a welder inhales such fumes in large quantities over a long period, there is a risk of developing various respiratory system diseases (RSDs). Methods: We developed quantitative frameworks to recognize the genetic effects of WFs on the development of RSDs. We analyzed Gene Expression microarray data from WFs exposed tissues and RSDs including Chronic Bronchitis (CB), Asthma (AS), Pulmonary Edema (PE), Lung Cancer (LC) datasets. We built disease-gene (diseasome) association networks and identified dysregulated signaling and ontological pathways, and protein-protein interaction sub-network using neighborhood-based benchmarking and multilayer networ...
With an increasing demand for stringent security systems, automated identification of individuals... more With an increasing demand for stringent security systems, automated identification of individuals based on biometric methods has been a major focus of research and development over the last decade. Biometric recognition analyses unique physiological traits or behavioral characteristics, such as an iris, face, retina, voice, fingerprint, hand geometry, keystrokes or gait. The iris has a complex and unique structure that remains stable over a person's lifetime, features that have led to its increasing interest in its use for biometric recognition. In this study, we proposed a technique incorporating Principal Component Analysis (PCA) based on Discrete Wavelet Transformation (DWT) for the extraction of the optimum features of an iris and reducing the runtime needed for iris templates classification. The idea of using DWT behind PCA is to reduce the resolution of the iris template. DWT converts an iris image into four frequency sub-bands. One frequency sub-band instead of four has b...
Journal of clinical bioinformatics, 2014
The diagnosis of comorbidities, which refers to the coexistence of different acute and chronic di... more The diagnosis of comorbidities, which refers to the coexistence of different acute and chronic diseases, is difficult due to the modern extreme specialisation of physicians. We envisage that a software dedicated to comorbidity diagnosis could result in an effective aid to the health practice. We have developed an R software comoR to compute novel estimators of the disease comorbidity associations. Starting from an initial diagnosis, genetic and clinical data of a patient the software identifies the risk of disease comorbidity. Then it provides a pipeline with different causal inference packages (e.g. pcalg, qtlnet etc) to predict the causal relationship of diseases. It also provides a pipeline with network regression and survival analysis tools (e.g. Net-Cox, rbsurv etc) to predict more accurate survival probability of patients. The input of this software is the initial diagnosis for a patient and the output provides evidences of disease comorbidity mapping. The functions of the com...
Daffodil International University Journal of Science and Technology, 2010
This research is concerned with the development of speech recognition front-end for segmenting an... more This research is concerned with the development of speech recognition front-end for segmenting and clustering continuous Bangla speech sentence to some predefined clusters. From the study of different previous research works it was observed that the front-end is an important part of any speech recognition system. In our work, the original speech sentences were recorded and stored as RIFF (.wav) file format. Then a segmentation approach was used to segment the continuous speech into uniquely identifiable and meaningful units. Among the different techniques, the word/sub-word segmentation is simple and produces very good results. This is why this technique was selected for speech segmentation to obtain improved performance. After segmentation, the segmented words were clustered into different clusters according to the number of syllables and the sizes of the segmented words. The test database contained 758 words/sub-words segmented from 120 sentences. Each sentence was recorded from s...
BMC Bioinformatics, 2012
Background: This work focuses on the computational modelling of osteomyelitis, a bone pathology c... more Background: This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure. Results: Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way. Conclusions: We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics.
Uploads
Papers by Dr Mohammad Ali Moni