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14 result(s) for 'author#Sanghamitra Bandyopadhyay' within BMC
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Citation: BMC Proceedings 2021 15(Suppl 11):17
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BMC Genomics reviewer acknowledgement 2015
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Citation: BMC Genomics 2016 17:168 -
S-conLSH: alignment-free gapped mapping of noisy long reads
The advancement of SMRT technology has unfolded new opportunities of genome analysis with its longer read length and low GC bias. Alignment of the reads to their appropriate positions in the respective referen...
Citation: BMC Bioinformatics 2021 22:64 -
A NMF based approach for integrating multiple data sources to predict HIV-1–human PPIs
Predicting novel interactions between HIV-1 and human proteins contributes most promising area in HIV research. Prediction is generally guided by some classification and inference based methods using single bi...
Citation: BMC Bioinformatics 2016 17:121 -
Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes
The landscape of biological and biomedical research is being changed rapidly with the invention of microarrays which enables simultaneous view on the transcription levels of a huge number of genes across diffe...
Citation: BMC Bioinformatics 2009 10:27 -
Journal of Translational Medicine reviewer acknowledgement 2015
Citation: Journal of Translational Medicine 2016 14:70 -
Development of the human cancer microRNA network
MicroRNAs are a class of small noncoding RNAs that are abnormally expressed in different cancer cells. Molecular signature of miRNAs in different malignancies suggests that these are not only actively involved...
Citation: Silence 2010 1:6 -
SFSSClass: an integrated approach for miRNA based tumor classification
MicroRNA (miRNA) expression profiling data has recently been found to be particularly important in cancer research and can be used as a diagnostic and prognostic tool. Current approaches of tumor classificatio...
Citation: BMC Bioinformatics 2010 11(Suppl 1):S22 -
Analyzing miRNA co-expression networks to explore TF-miRNA regulation
Current microRNA (miRNA) research in progress has engendered rapid accumulation of expression data evolving from microarray experiments. Such experiments are generally performed over different tissues belongin...
Citation: BMC Bioinformatics 2009 10:163 -
PuTmiR: A database for extracting neighboring transcription factors of human microRNAs
Some of the recent investigations in systems biology have revealed the existence of a complex regulatory network between genes, microRNAs (miRNAs) and transcription factors (TFs). In this paper, we focus on TF...
Citation: BMC Bioinformatics 2010 11:190 -
Coexpression and coregulation analysis of time-series gene expression data in estrogen-induced breast cancer cell
Estrogen is a chemical messenger that has an influence on many breast cancers as it helps cells to grow and divide. These cancers are often known as estrogen responsive cancers in which estrogen receptor occup...
Citation: Algorithms for Molecular Biology 2013 8:9 -
A multiobjective approach for identifying protein complexes and studying their association in multiple disorders
Detecting protein complexes within protein–protein interaction (PPI) networks is a major step toward the analysis of biological processes and pathways. Identification and characterization of protein complexes ...
Citation: Algorithms for Molecular Biology 2015 10:24 -
Detecting TF-miRNA-gene network based modules for 5hmC and 5mC brain samples: a intra- and inter-species case-study between human and rhesus
Study of epigenetics is currently a high-impact research topic. Multi stage methylation is also an area of high-dimensional prospect. In this article, we provide a new study (intra and inter-species study) on ...
Citation: BMC Genetics 2018 19:9 -
Biological networks in Parkinson’s disease: an insight into the epigenetic mechanisms associated with this disease
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorders in the world. Studying PD from systems biology perspective involving genes and their regulators might provide deeper insights i...
Citation: BMC Genomics 2017 18:721