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M. Mondal Ananda
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2020 – today
- 2024
- [c24]Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mondal, Hua Wei, Dongsheng Luo:
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks. ICML 2024 - [i1]Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo:
Interpreting Graph Neural Networks with In-Distributed Proxies. CoRR abs/2402.02036 (2024) - 2023
- [c23]Masrur Sobhan, Ananda Mohan Mondal
:
Evaluating SHAP's Robustness in Precision Medicine: Effect of Filtering and Normalization. BIBM 2023: 3157-3164 - [c22]Raihanul Bari Tanvir, Ricardo Ruiz, Samuel Ebert, Masrur Sobhan, Abdullah Al Mamun, Ananda Mohan Mondal:
Quantifying Intratumor Heterogeneity by Key Genes Selected Using Concrete Autoencoder. PReMI 2023: 844-852 - 2022
- [c21]Masrur Sobhan, Ananda Mohan Mondal
:
Explainable Machine Learning to Identify Patient-specific Biomarkers for Lung Cancer. BIBM 2022: 3152-3159 - [c20]Raihanul Bari Tanvir, Masrur Sobhan, Ananda Mohan Mondal
:
An Autoencoder Based Bioinformatics Framework for Predicting Prognosis of Breast Cancer Patients. BIBM 2022: 3160-3166 - [c19]Masrur Sobhan, Daniela Leizaola, Anuradha Godavarty, Ananda Mohan Mondal
:
Subject Skin Tone Classification with Implications in Wound Imaging using Deep Learning. CSCI 2022: 1640-1645 - [e1]Donald A. Adjeroh, Qi Long, Xinghua Mindy Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda Mondal, Jin Liu:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, NV, USA, December 6-8, 2022. IEEE 2022, ISBN 978-1-6654-6819-0 [contents] - 2020
- [j4]Mona Maharjan, Raihanul Bari Tanvir, Kamal Chowdhury, Wenrui Duan
, Ananda Mohan Mondal
:
Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies. BMC Bioinform. 21-S(9): 218 (2020) - [c18]Raihanul Bari Tanvir, Ananda Mohan Mondal
:
Stage-Specific Co-expression Network Analysis for Cancer Biomarker Discovery. BIBM 2020: 1813-1819 - [c17]Abdullah Al Mamun, Wenrui Duan, Ananda Mohan Mondal
:
Pan-cancer Feature Selection and Classification Reveals Important Long Non-coding RNAs. BIBM 2020: 2417-2424 - [c16]Abdullah Al Mamun, Masrur Sobhan, Raihanul Bari Tanvir, Charles J. Dimitroff
, Ananda Mohan Mondal
:
Deep Learning to Discover Cancer Glycome Genes Signifying the Origins of Cancer. BIBM 2020: 2425-2431 - [c15]Masrur Sobhan, Abdullah Al Mamun, Raihanul Bari Tanvir, Mario Jacas Alfonso, Pablo Valle, Ananda Mohan Mondal
:
Deep Learning to Discover Genomic Signatures for Racial Disparity in Lung Cancer. BIBM 2020: 2990-2992
2010 – 2019
- 2019
- [j3]Raihanul Bari Tanvir, Tasmia Aqila, Mona Maharjan, Abdullah Al Mamun, Ananda Mohan Mondal
:
Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer. Data 4(2): 81 (2019) - [c14]Abdullah Al Mamun, Ananda Mohan Mondal:
Long Non-coding RNA Based Cancer Classification using Deep Neural Networks. BCB 2019: 541 - [c13]Tasmia Aqila, Ananda Mohan Mondal:
Pseudotime Based Analysis of Cancer Dynamics. BCB 2019: 544 - [c12]Raihanul Bari Tanvir, Mona Maharjan, Ananda Mohan Mondal:
Community Based Cancer Biomarker Identification from Gene Co-expression Network. BCB 2019: 545 - [c11]Nelson Zange Tsaku, Sai Chandra Kosaraju
, Tasmia Aqila, Mohammad Masum
, Dae Hyun Song, Ananda Mohan Mondal
, Hyun Min Koh, Mingon Kang:
Texture-based Deep Learning for Effective Histopathological Cancer Image Classification. BIBM 2019: 973-977 - [c10]Tasmia Aqila, Abdullah Al Mamun, Ananda Mohan Mondal
:
Pseudotime Based Discovery of Breast Cancer Heterogeneity. BIBM 2019: 2049-2054 - [c9]Raihanul Bari Tanvir, Ananda Mohan Mondal
:
Cancer Biomarker Discovery from Gene Co-expression Networks Using Community Detection Methods. BIBM 2019: 2097-2104 - [c8]Abdullah Al Mamun, Ananda Mohan Mondal
:
Feature Selection and Classification Reveal Key lncRNAs for Multiple Cancers. BIBM 2019: 2825-2831 - 2018
- [c7]Ananda Mohan Mondal
, Cornelia Ada Schultz, Markea Sheppard, Jasmine Carson, Raihanul Bari Tanvir, Tasmia Aqila:
Graph Theoretic Concepts as the Building Blocks for Disease Initiation and Progression at Protein Network Level: Identification and Challenges. BIBM 2018: 2713-2719 - 2015
- [c6]Dominic K. Bett, Ananda Mohan Mondal
:
Diffusion kernel to identify missing PPIs in protein network biomarker. BIBM 2015: 1614-1619 - 2014
- [j2]Ananda Mondal
, Jianjun Hu:
Network based prediction of protein localisation using diffusion Kernel. Int. J. Data Min. Bioinform. 9(4): 386-400 (2014) - [c5]Prayas Timalsina, Kevin Charles, Ananda Mohan Mondal
:
STRING PPI Score to Characterize Protein Subnetwork Biomarkers for Human Diseases and Pathways. BIBE 2014: 251-256 - 2013
- [c4]Ananda Mohan Mondal, Jianjun Hu:
Scored Protein-Protein Interaction to Predict Subcellular Localizations for Yeast Using Diffusion Kernel. PReMI 2013: 647-655 - 2012
- [j1]Jhih-rong Lin, Ananda Mondal
, Rong Liu, Jianjun Hu:
Minimalist ensemble algorithms for genome-wide protein localization prediction. BMC Bioinform. 13: 157 (2012) - [c3]Ananda Mohan Mondal, Jianjun Hu:
Mutation analysis of disease causing proteins. BIBM Workshops 2012: 975-977 - 2011
- [c2]M. Mondal Ananda, Jhih-rong Lin, Jianjun Hu:
Network based subcellular localization prediction for multi-label proteins. BIBM Workshops 2011: 473-480 - 2010
- [c1]M. Mondal Ananda, Jianjun Hu:
NetLoc: Network based protein localization prediction using protein-protein interaction and co-expression networks. BIBM 2010: 142-148
Coauthor Index
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last updated on 2024-09-02 20:29 CEST by the dblp team
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