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Musfiqur Sazal

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Scientific Reports|March 12, 2021
Causal effects in microbiomes using interventional calculusMusfiqur Sazal, Vitalii Stebliankin, Kalai Mathee, et al.
Microbial Genomics|February 7, 2023
A novel approach for combining the metagenome, metaresistome, metareplicome and causal inference to determine the microbes and their antibiotic resistance gene repertoire that contribute to dysbiosisVitalii Stebliankin, Musfiqur Sazal, Camilo Valdes, et al.
BMC Genomics|December 22, 2020
Inferring directional relationships in microbial communities using signed Bayesian networksMusfiqur Sazal, Kalai Mathee, Daniel Ruiz-Perez, et al.
Msystems|September 6, 2024
Unfolding and de-confounding: biologically meaningful causal inference from longitudinal multi-omic networks using METALICADaniel Ruiz-Perez, Isabella Gimon, Musfiqur Sazal, et al.
Biorxiv : the Preprint Server for Biology|January 3, 2024
Unfolding and De-confounding: Biologically meaningful causal inference from longitudinal multi-omic networks using METALICADaniel Ruiz-Perez, Isabella Gimon, Musfiqur Sazal, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Scientific Reports|March 12, 2021
Causal effects in microbiomes using interventional calculusMusfiqur Sazal, Vitalii Stebliankin, Kalai Mathee, et al.
Microbial Genomics|February 7, 2023
A novel approach for combining the metagenome, metaresistome, metareplicome and causal inference to determine the microbes and their antibiotic resistance gene repertoire that contribute to dysbiosisVitalii Stebliankin, Musfiqur Sazal, Camilo Valdes, et al.
BMC Genomics|December 22, 2020
Inferring directional relationships in microbial communities using signed Bayesian networksMusfiqur Sazal, Kalai Mathee, Daniel Ruiz-Perez, et al.
Msystems|September 6, 2024
Unfolding and de-confounding: biologically meaningful causal inference from longitudinal multi-omic networks using METALICADaniel Ruiz-Perez, Isabella Gimon, Musfiqur Sazal, et al.
Biorxiv : the Preprint Server for Biology|January 3, 2024
Unfolding and De-confounding: Biologically meaningful causal inference from longitudinal multi-omic networks using METALICADaniel Ruiz-Perez, Isabella Gimon, Musfiqur Sazal, et al.
Pageof 1