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Riasat Azim

Showing results (1-10 of 11) with videos related to

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Cell Cycle (Georgetown, Tex.)|September 17, 2021
Cell-specific gene association network construction from single-cell RNA sequenceRiasat Azim, Shulin Wang
Briefings in Bioinformatics|February 2, 2026
Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?Fahim Hafiz, Riasat Azim, Swakkhar Shatabda
Computers in Biology and Medicine|June 25, 2022
CDSImpute: An ensemble similarity imputation method for single-cell RNA sequence dropoutsRiasat Azim, Shulin Wang, Shoaib Ahmed Dipu
Cell Cycle (Georgetown, Tex.)|July 7, 2020
Purity estimation from differentially methylated sites using Illumina Infinium methylation microarray dataRiasat Azim, Shulin Wang, Su Zhou, et al.
Computers in Biology and Medicine|April 27, 2025
GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association predictionUmmay Maria Muna, Fahim Hafiz, Shanta Biswas, et al.
Computational Biology and Chemistry|February 15, 2020
Predicting potential miRNA-disease associations by combining gradient boosting decision tree with logistic regressionSu Zhou, Shulin Wang, Qi Wu, et al.
Bioinformatics Advances|June 8, 2026
Trainable clustering framework for spatial transcriptomicsRiasat Azim, Sabab Aosaf, Swakkhar Shatabda, et al.
Briefings in Bioinformatics|April 15, 2026
The good, the bad, and the ugly: opportunities, challenges, and pitfalls in spatial proteomics modelingShahil Yasar Haque, Swakkhar Shatabda, Salekul Islam, et al.
Computers in Biology and Medicine|April 8, 2023
A patient-specific functional module and path identification technique from RNA-seq dataRiasat Azim, Shulin Wang, Shoaib Ahmed Dipu, et al.
Computer Methods and Programs in Biomedicine|March 27, 2025
Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow NetworkSimon Bin Akter, Sumya Akter, Rakibul Hasan, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Cell Cycle (Georgetown, Tex.)|September 17, 2021
Cell-specific gene association network construction from single-cell RNA sequenceRiasat Azim, Shulin Wang
Briefings in Bioinformatics|February 2, 2026
Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?Fahim Hafiz, Riasat Azim, Swakkhar Shatabda
Computers in Biology and Medicine|June 25, 2022
CDSImpute: An ensemble similarity imputation method for single-cell RNA sequence dropoutsRiasat Azim, Shulin Wang, Shoaib Ahmed Dipu
Cell Cycle (Georgetown, Tex.)|July 7, 2020
Purity estimation from differentially methylated sites using Illumina Infinium methylation microarray dataRiasat Azim, Shulin Wang, Su Zhou, et al.
Computers in Biology and Medicine|April 27, 2025
GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association predictionUmmay Maria Muna, Fahim Hafiz, Shanta Biswas, et al.
Computational Biology and Chemistry|February 15, 2020
Predicting potential miRNA-disease associations by combining gradient boosting decision tree with logistic regressionSu Zhou, Shulin Wang, Qi Wu, et al.
Bioinformatics Advances|June 8, 2026
Trainable clustering framework for spatial transcriptomicsRiasat Azim, Sabab Aosaf, Swakkhar Shatabda, et al.
Briefings in Bioinformatics|April 15, 2026
The good, the bad, and the ugly: opportunities, challenges, and pitfalls in spatial proteomics modelingShahil Yasar Haque, Swakkhar Shatabda, Salekul Islam, et al.
Computers in Biology and Medicine|April 8, 2023
A patient-specific functional module and path identification technique from RNA-seq dataRiasat Azim, Shulin Wang, Shoaib Ahmed Dipu, et al.
Computer Methods and Programs in Biomedicine|March 27, 2025
Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow NetworkSimon Bin Akter, Sumya Akter, Rakibul Hasan, et al.
Pageof 2