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Alioune Ngom
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Publications
- 2024
- [i3]Seyedeh Shaghayegh Sadeghi, Alan Bui, Ali Forooghi, Jianguo Lu, Alioune Ngom:
Comparative Analysis of LLaMA and ChatGPT Embeddings for Molecule Embedding. CoRR abs/2402.00024 (2024) - 2022
- [j33]Seyedeh Shaghayegh Sadeghi, Jianguo Lu, Alioune Ngom:
A network-based drug repurposing method via non-negative matrix factorization. Bioinform. 38(5): 1369-1377 (2022) - [j32]Forough Firoozbakht, Iman Rezaeian, Luis Rueda, Alioune Ngom:
Computationally repurposing drugs for breast cancer subtypes using a network-based approach. BMC Bioinform. 23(1): 143 (2022) - [c71]Alexandru Filip, Seyedeh Shaghayegh Sadeghi, Alioune Ngom, Luis Rueda:
DeePSLiM: A Deep Learning Approach to Identify Predictive Short-linear Motifs for Protein Sequence Classification. CIBCB 2022: 1-8 - [c70]Seyedeh Shaghayegh Sadeghi, Alioune Ngom:
DDIPred: Graph Convolutional Network-Based Drug-drug Interactions Prediction Using Drug Chemical Structure Embedding. CIBCB 2022: 1-6 - 2020
- [j31]Sheikh Jubair, Abedalrhman Alkhateeb, Ashraf Abou Tabl, Luis Rueda, Alioune Ngom:
A novel approach to identify subtype-specific network biomarkers of breast cancer survivability. Netw. Model. Anal. Health Informatics Bioinform. 9(1): 43 (2020) - [c69]Huy Quang Pham, Luis Rueda, Alioune Ngom:
A Data Integration Approach for Detecting Biomarkers of Breast Cancer Survivability. IWBBIO 2020: 49-60 - [c68]Mohammad Anas Shah, Abdala Nour, Alioune Ngom, Luis Rueda:
Cancer Detection Based on Image Classification by Using Convolution Neural Network. IWBBIO 2020: 275-286 - 2019
- [c66]Huy Quang Pham, Jurko Guba, Mousa Gawanmeh, Lisa A. Porter, Alioune Ngom:
A Network-based Machine Learning Approach for Identifying Biomarkers of Breast Cancer Survivability. BCB 2019: 639-644 - 2018
- [j30]Yifeng Li, Fang-Xiang Wu, Alioune Ngom:
A review on machine learning principles for multi-view biological data integration. Briefings Bioinform. 19(2): 325-340 (2018) - [j29]Yixun Li, Mina Maleki, Nicholas J. Carruthers, Paul M. Stemmer, Alioune Ngom, Luis Rueda:
The predictive performance of short-linear motif features in the prediction of calmodulin-binding proteins. BMC Bioinform. 19-S(14): 13-25 (2018) - [c64]Sheikh Jubair, Luis Rueda, Alioune Ngom:
Identifying suutype specific network-Uiomarkers of breast cancer survivauility. IJCNN 2018: 1-9 - [c63]Ashraf Abou Tabl, Abedalrhman Alkhateeb, Luis Rueda, Waguih H. ElMaraghy, Alioune Ngom:
Identification of the Treatment Survivability Gene Biomarkers of Breast Cancer Patients via a Tree-Based Approach. IWBBIO (1) 2018: 166-176 - 2017
- [j28]Forough Firoozbakht, Iman Rezaeian, Michele D'agnillo, Lisa A. Porter, Luis Rueda, Alioune Ngom:
An Integrative Approach for Identifying Network Biomarkers of Breast Cancer Subtypes Using Genomic, Interactomic, and Transcriptomic Data. J. Comput. Biol. 24(8): 756-766 (2017) - [c62]Naveen Mangalakumar, Abed Alkhateeb, Huy Quang Pham, Luis Rueda, Alioune Ngom:
Outlier Genes as Biomarkers of Breast Cancer Survivability in Time-Series Data. BCB 2017: 594 - [c61]Ashraf Abou Tabl, Abed Alkhateeb, Waguih H. ElMaraghy, Alioune Ngom:
Machine Learning Model for Identifying Gene Biomarkers for Breast Cancer Treatment Survival. BCB 2017: 607 - [c60]Huy Quang Pham, Luis Rueda, Alioune Ngom:
Predicting Breast Cancer Outcome under Different Treatments by Feature Selection Approaches. BCB 2017: 617 - [c59]Yixun Li, Mina Maleki, Nicholas J. Carruthers, Luis Rueda, Paul M. Stemmer, Alioune Ngom:
Prediction of Calmodulin-Binding Proteins Using Short-Linear Motifs. IWBBIO (2) 2017: 107-117 - 2016
- [j27]Yifeng Li, Haifen Chen, Jie Zheng, Alioune Ngom:
The Max-Min High-Order Dynamic Bayesian Network for Learning Gene Regulatory Networks with Time-Delayed Regulations. IEEE ACM Trans. Comput. Biol. Bioinform. 13(4): 792-803 (2016) - [c58]Huy Quang Pham, Alioune Ngom, Luis Rueda:
A new feature selection approach for optimizing prediction models, applied to breast cancer subtype classification. BIBM 2016: 1535-1541 - [c57]Huy Quang Pham, Alioune Ngom, Luis Rueda:
PAFS - An efficient method for classifier-specific feature selection. SSCI 2016: 1-8 - [i1]Iman Rezaeian, Eliseos J. Mucaki, Katherina Baranova, Huy Quang Pham, Dimo Angelov, Alioune Ngom, Luis Rueda, Peter K. Rogan:
Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning. F1000Research 5: 2124 (2016) - 2015
- [j25]Yifeng Li, B. John Oommen, Alioune Ngom, Luis Rueda:
Pattern classification using a new border identification paradigm: The nearest border technique. Neurocomputing 157: 105-117 (2015) - [c56]Forough Firoozbakht, Iman Rezaeian, Alioune Ngom, Luis Rueda:
A new compact set of biomarkers for distinguishing among ten breast cancer subtypes. BIBM 2015: 1579-1585 - [c55]Yifeng Li, Alioune Ngom:
Data integration in machine learning. BIBM 2015: 1665-1671 - [c54]Forough Firoozbakht, Iman Rezaeian, Alioune Ngom, Luis Rueda, Lisa A. Porter:
A novel approach for finding informative genes in ten subtypes of breast cancer. CIBCB 2015: 1-6 - [c53]Yixun Li, Behzad Rezaei, Alioune Ngom, Luis Rueda:
Prediction of high-throughput protein-protein interactions based on protein sequence information. CIBCB 2015: 1-6 - 2014
- [j24]Xing-Ming Zhao, Alioune Ngom, Jin-Kao Hao:
Pattern recognition in bioinformatics. Neurocomputing 145: 1-2 (2014) - [j23]Yifeng Li, Alioune Ngom:
Versatile sparse matrix factorization: Theory and applications. Neurocomputing 145: 23-29 (2014) - [j22]Elena Marchiori, Alioune Ngom, Raj Acharya:
Guest Editorial: Pattern Recognition in Bioinformatics. IEEE ACM Trans. Comput. Biol. Bioinform. 11(3): 498-499 (2014) - [c52]Yifeng Li, Richard J. Caron, Alioune Ngom:
A decomposition method for large-scale sparse coding in representation learning. IJCNN 2014: 3732-3738 - [e4]Matteo Comin, Lukas Käll, Elena Marchiori, Alioune Ngom, Jagath C. Rajapakse:
Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings. Lecture Notes in Computer Science 8626, Springer 2014, ISBN 978-3-319-09191-4 [contents] - 2013
- [j21]Yifeng Li, Alioune Ngom:
Sparse representation approaches for the classification of high-dimensional biological data. BMC Syst. Biol. 7(S-4): S6 (2013) - [j20]Yifeng Li, Alioune Ngom:
Classification approach based on non-negative least squares. Neurocomputing 118: 41-57 (2013) - [j19]Yifeng Li, Alioune Ngom:
The non-negative matrix factorization toolbox for biological data mining. Source Code Biol. Medicine 8: 10 (2013) - [j18]Yifeng Li, Alioune Ngom:
Nonnegative Least-Squares Methods for the Classification of High-Dimensional Biological Data. IEEE ACM Trans. Comput. Biol. Bioinform. 10(2): 447-456 (2013) - [c51]Yifeng Li, B. John Oommen, Alioune Ngom, Luis Rueda:
A New Paradigm for Pattern Classification: Nearest Border Techniques. Australasian Conference on Artificial Intelligence 2013: 441-446 - [c50]Manish Pandit, Luis Rueda, Alioune Ngom:
Prediction of Biological Protein-protein Interaction Types Using Short-Linear Motifs. BCB 2013: 698 - [c49]Yifeng Li, Alioune Ngom:
The max-min high-order dynamic Bayesian network learning for identifying gene regulatory networks from time-series microarray data. CIBCB 2013: 83-90 - [c46]Yifeng Li, Alioune Ngom:
Versatile Sparse Matrix Factorization and Its Applications in High-Dimensional Biological Data Analysis. PRIB 2013: 91-101 - [c45]Iman Rezaeian, Yifeng Li, Martin Crozier, Eran Andrechek, Alioune Ngom, Luis Rueda, Lisa A. Porter:
Identifying Informative Genes for Prediction of Breast Cancer Subtypes. PRIB 2013: 138-148 - [e3]Alioune Ngom, Enrico Formenti, Jin-Kao Hao, Xing-Ming Zhao, Twan van Laarhoven:
Pattern Recognition in Bioinformatics - 8th IAPR International Conference, PRIB 2013, Nice, France, June 17-20, 2013. Proceedings. Lecture Notes in Computer Science 7986, Springer 2013, ISBN 978-3-642-39158-3 [contents] - 2012
- [c44]Yifeng Li, Alioune Ngom:
Fast sparse representation approaches for the classification of high-dimensional biological data. BIBM 2012: 1-6 - [c43]Yifeng Li, Alioune Ngom:
A new Kernel non-negative matrix factorization and its application in microarray data analysis. CIBCB 2012: 371-378 - [c42]Yifeng Li, Alioune Ngom:
Fast Kernel Sparse Representation Approaches for Classification. ICDM 2012: 966-971 - [c41]Yifeng Li, Alioune Ngom:
Supervised Dictionary Learning via Non-negative Matrix Factorization for Classification. ICMLA (1) 2012: 439-443 - [c40]Yifeng Li, Alioune Ngom, Luis Rueda:
A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm. PRIB 2012: 38-48 - [c39]Yifeng Li, Alioune Ngom:
Diagnose the Premalignant Pancreatic Cancer Using High Dimensional Linear Machine. PRIB 2012: 198-209 - 2011
- [j17]Darío Rojas, Luis Rueda, Alioune Ngom, Homero Urrutia, Gerardo Carcamo:
Image segmentation of biofilm structures using optimal multi-level thresholding. Int. J. Data Min. Bioinform. 5(3): 266-286 (2011) - [c38]Amirali Jafarian, Alioune Ngom, Luis Rueda:
A Novel Recursive Feature Subset Selection Algorithm. BIBE 2011: 78-83 - [c37]Amirali Jafarian, Alioune Ngom:
A new gene subset selection approach based on linearly separating gene pairs. ICCABS 2011: 105-110 - [c36]Amirali Jafarian, Alioune Ngom, Luis Rueda:
New Gene Subset Selection Approaches Based on Linear Separating Genes and Gene-Pairs. PRIB 2011: 50-62 - 2010
- [j15]Numanul Subhani, Luis Rueda, Alioune Ngom, Conrad J. Burden:
Multiple gene expression profile alignment for microarray time-series data clustering. Bioinform. 26(18): 2281-2288 (2010) - [j14]Madhu Chetty, Alioune Ngom, Elena Marchiori:
Computational Intelligence in Bioinformatics. Neurocomputing 73(13-15): 2291-2292 (2010) - [j13]Laleh Soltan Ghoraie, Robin Gras, Lili Wang, Alioune Ngom:
Optimal decoding and minimal length for the non-unique oligonucleotide probe selection problem. Neurocomputing 73(13-15): 2407-2418 (2010) - [j12]Xin Wu, Arunita Jaekel, Ataul Bari, Alioune Ngom:
Optimized Hybrid Resource Allocation in Wireless Cellular Networks with and without Channel Reassignment. J. Comput. Networks Commun. 2010: 524854:1-524854:11 (2010) - [j11]Alioune Ngom, Luis Rueda, Lili Wang, Robin Gras:
Selection based heuristics for the non-unique oligonucleotide probe selection problem in microarray design. Pattern Recognit. Lett. 31(14): 2113-2125 (2010) - [c35]Yifeng Li, Numanul Subhani, Alioune Ngom, Luis Rueda:
Alignment-based versus variation-based transformation methods for clustering microarray time-series data. BCB 2010: 53-61 - [c33]Yifeng Li, Alioune Ngom:
Non-negative matrix and tensor factorization based classification of clinical microarray gene expression data. BIBM 2010: 438-443 - [c32]Numanul Subhani, Yifeng Li, Alioune Ngom, Luis Rueda:
Alignment versus variation methods for clustering microarray time-series data. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c31]Yifeng Li, Alioune Ngom:
Classification of Clinical Gene-Sample-Time Microarray Expression Data via Tensor Decomposition Methods. CIBB 2010: 275-286 - [c30]Yifeng Li, Alioune Ngom, Luis Rueda:
Missing value imputation methods for gene-sample-time microarray data analysis. CIBCB 2010: 1-7 - [c29]Numanul Subhani, Luis Rueda, Alioune Ngom, Conrad J. Burden:
New approaches to clustering microarray time-series data using multiple expression profile alignment. CIBCB 2010: 1-7 - 2009
- [c26]Darío Rojas, Luis Rueda, Alioune Ngom, Homero Urrutia, Gerardo Carcamo:
Biofilm Image Segmentation Using Optimal Multi-level Thresholding. BIBM 2009: 185-190 - [c23]Xin Wu, Arunita Jaekel, Ataul Bari, Alioune Ngom:
Optimized Hybrid Resource Allocation in Wireless Cellular Networks with and without Channel Reassignment. ITNG 2009: 1146-1151 - [c22]Darío Rojas, Luis Rueda, Homero Urrutia, Alioune Ngom:
Efficient Optimal Multi-level Thresholding for Biofilm Image Segmentation. PRIB 2009: 307-318 - [c21]Laleh Soltan Ghoraie, Robin Gras, Lili Wang, Alioune Ngom:
Bayesian Optimization Algorithm for the Non-unique Oligonucleotide Probe Selection Problem. PRIB 2009: 365-376 - [c20]Numanul Subhani, Alioune Ngom, Luis Rueda, Conrad J. Burden:
Microarray Time-Series Data Clustering via Multiple Alignment of Gene Expression Profiles. PRIB 2009: 377-390 - 2008
- [j10]Luis Rueda, Ataul Bari, Alioune Ngom:
Clustering Time-Series Gene Expression Data with Unequal Time Intervals. Trans. Comp. Sys. Biology 10: 100-123 (2008) - [j9]Lili Wang, Alioune Ngom, Robin Gras, Luis Rueda:
An Evolutionary Approach to the Non-unique Oligonucleotide Probe Selection Problem. Trans. Comp. Sys. Biology 10: 143-162 (2008) - [c19]Lili Wang, Alioune Ngom, Robin Gras:
Non-unique oligonucleotide microarray probe selection method based on genetic algorithms. IEEE Congress on Evolutionary Computation 2008: 1004-1010 - [c18]Lili Wang, Alioune Ngom, Robin Gras, Luis Rueda:
Evolution strategy with greedy probe selection heuristics for the non-unique oligonucleotide probe selection problem. CIBCB 2008: 54-61 - [c17]Lili Wang, Alioune Ngom, Luis Rueda:
Sequential Forward Selection Approach to the Non-unique Oligonucleotide Probe Selection Problem. PRIB 2008: 262-275 - [e2]Madhu Chetty, Alioune Ngom, Shandar Ahmad:
Pattern Recognition in Bioinformatics, Third IAPR International Conference, PRIB 2008, Melbourne, Australia, October 15-17, 2008. Proceedings. Lecture Notes in Computer Science 5265, Springer 2008, ISBN 978-3-540-88434-7 [contents] - 2007
- [j8]Wei Yang, Luis Rueda, Alioune Ngom:
On Finding the Best Parameters of Fuzzy k-Means for Clustering Microarray Data. J. Multiple Valued Log. Soft Comput. 13(1-2): 145-178 (2007) - [c15]Lili Wang, Alioune Ngom:
A Model-Based Approach to the Non-Unique Oligonucleotide Probe Selection Problem. BIONETICS 2007: 209-215 - 2005
- [c12]Leon French, Alioune Ngom, Luis Rueda:
Fast Protein Superfamily Classification Using Principal Component Null Space Analysis. Canadian AI 2005: 158-169 - [c11]Mona Aggarwal, Robert D. Kent, Alioune Ngom:
Genetic Algorithm Based Scheduler for Computational Grids. HPCS 2005: 209-215 - [c10]Wei Yang, Luis Rueda, Alioune Ngom:
A simulated annealing approach to find the optimal parameters for fuzzy clustering microarray data. SCCC 2005: 45-54 - 2004
- [c8]Luis Rueda, Alioune Ngom:
An Empirical Evaluation of the Classification Error of Two Thresholding Methods for Fisher's Classifier. IC-AI 2004: 837-842
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last updated on 2024-02-15 19:28 CET by the dblp team
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