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miRbiom: Machine-Learning on Bayesian Causal Nets of RBP-miRNA interactions successfully predicts miRNA profiles
Upendra Kumar Pradhan, Nitesh Kumar Sharma, Prakash Kumar, Ashwani Kumar, Sagar Gupta, Ravi Shankar
doi: https://doi.org/10.1101/2020.06.18.156851
Upendra Kumar Pradhan
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
2Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh-201 002
3ICAR-Indian Agricultural Statistics Research Institute Library Avenue, Pusa, New Delhi, Delhi 110012
Nitesh Kumar Sharma
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
2Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh-201 002
Prakash Kumar
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
2Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh-201 002
3ICAR-Indian Agricultural Statistics Research Institute Library Avenue, Pusa, New Delhi, Delhi 110012
Ashwani Kumar
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
Sagar Gupta
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
Ravi Shankar
1Studio of Computational Biology & Bioinformatics, CSIR-Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur (HP), 176061, India
2Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh-201 002

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Posted September 07, 2021.
miRbiom: Machine-Learning on Bayesian Causal Nets of RBP-miRNA interactions successfully predicts miRNA profiles
Upendra Kumar Pradhan, Nitesh Kumar Sharma, Prakash Kumar, Ashwani Kumar, Sagar Gupta, Ravi Shankar
bioRxiv 2020.06.18.156851; doi: https://doi.org/10.1101/2020.06.18.156851
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