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Papers by Alan Liew

Research paper thumbnail of Sequence-based prediction of protein-peptide binding sites using support vector machine

Journal of computational chemistry, Jan 2, 2016

Protein-peptide interactions are essential for all cellular processes including DNA repair, repli... more Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computationally as the first step. All existing approaches for predicting protein-peptide binding sites, however, are based on protein structures despite the fact that the structures for most proteins are not yet solved. This article proposes the first machine-learning method called SPRINT to make Sequence-based prediction of Protein-peptide Residue-level Interactions. SPRINT yields a robust and consistent performance for 10-fold cross validations and independent test. The most important feature is evolution-generated sequence profiles. For the test set (1056 binding and non-binding residues), it yields a Matthews' Correlation Coefficient of 0.326 with a sensitivity of 64% and a specificity of 68%. This sequence-based technique shows comparable o...

Research paper thumbnail of Multiscale wavelet analysis of edges : issues of uniqueness & reconstruction

Research paper thumbnail of Modeling of Waiting Time Distribution in Kinetic States of Kinesin Nanomachine

Research paper thumbnail of Content based recommendation for HBB TV based on bayes conditional probability for multiple variables approach

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015

Research paper thumbnail of Measuring correlation between microarray time-series data using dominant spectral component

Proceedings of the Second Conference on Asia Pacific Bioinformatics Volume 29, 2004

Research paper thumbnail of Accurate Partial Volume Estimation of MR Brain Tissues

Research paper thumbnail of Microarray Image Analysis and Spot Segmentation

Research paper thumbnail of Reliable Detection of Short Periodic Gene Expression Time Series Profiles in DNA Microarray Data

2009 Ieee International Conference on Systems Man and Cybernetics, Oct 1, 2009

Research paper thumbnail of General Retinal Vessel Segmentation UsingRegularization-Based Multiconcavity Modeling

Research paper thumbnail of Recent Patents on Biclustering Algorithms for Gene Expression Data Analysis

Research paper thumbnail of Supp1 pfalcipuram ranking

ABSTRACT Please cite the following paper if you use this resource: ******************************... more ABSTRACT Please cite the following paper if you use this resource: ***************************************************************************************** A.W.C. Liew, J. Xian, S. Wu, D. Smith, and H. Yan, "Spectral Estimation in Unevenly Sampled Space of Periodically Expressed Microarray Time Series Data", BMC Bioinformatics, 8:137, 24 April 2007 *****************************************************************************************

Research paper thumbnail of Visual Speech Recognition: Lip Segmentation and Mapping

Research paper thumbnail of Missing value imputation for gene expression data: computational techniques to recover missing datafrom available information

Research paper thumbnail of Human Face Animation Based on Video Analysis, with Applications to Mobile Entertainment

Research paper thumbnail of Data Mining for Bioinformatics

Research paper thumbnail of Image Compression Concepts Overview

Research paper thumbnail of Content-Based Image Retrieval

Research paper thumbnail of Supp2 yeast ranking

Please cite the following paper if you use this resource: ***************************************... more Please cite the following paper if you use this resource: ***************************************************************************************** A.W.C. Liew, J. Xian, S. Wu, D. Smith, and H. Yan, "Spectral Estimation in Unevenly Sampled Space of Periodically Expressed Microarray Time Series Data", BMC Bioinformatics, 8:137, 24 April 2007 *****************************************************************************************

Research paper thumbnail of A novel OPTOC-based clustering algorithm for gene expression data analysis

Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint, 2003

Research paper thumbnail of Segmentation and Recognition of Multi-Model Photo Event

Neurocomputing, 2015

ABSTRACT Photograph becomes more and more convenient with the rapid growing of smart phones, whic... more ABSTRACT Photograph becomes more and more convenient with the rapid growing of smart phones, which makes photo become one of the most widely used social media. In this paper, we have proposed a segmentation and recognition method for multi-model photo event to help users organize and manage their increasing photo collections. Generative model of photo event is built by analyzing time, location, camera parameters and visual content of photos. Expectation-Maximization (EM) learning algorithm is applied to discover the best parameters of the proposed generative model. With the defined model, each photo is categorized into the corresponding event by calculating the maximum posteriori probability. The representativeness of an event is a photo collage constructed by selecting a set of representative photos from the corresponding event. The proposed method is characterized by the following properties: 1) unlike most of the existing photo event segmentation methods, the location of photos is treated as a key feature, 2) the representativeness of an event is a picture collage instead of a single photo, which is not only informative but also very appealing. The experimental results show that the proposed method is effective and efficient on the photo collections from three experienced smart phone users.

Research paper thumbnail of Sequence-based prediction of protein-peptide binding sites using support vector machine

Journal of computational chemistry, Jan 2, 2016

Protein-peptide interactions are essential for all cellular processes including DNA repair, repli... more Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computationally as the first step. All existing approaches for predicting protein-peptide binding sites, however, are based on protein structures despite the fact that the structures for most proteins are not yet solved. This article proposes the first machine-learning method called SPRINT to make Sequence-based prediction of Protein-peptide Residue-level Interactions. SPRINT yields a robust and consistent performance for 10-fold cross validations and independent test. The most important feature is evolution-generated sequence profiles. For the test set (1056 binding and non-binding residues), it yields a Matthews' Correlation Coefficient of 0.326 with a sensitivity of 64% and a specificity of 68%. This sequence-based technique shows comparable o...

Research paper thumbnail of Multiscale wavelet analysis of edges : issues of uniqueness & reconstruction

Research paper thumbnail of Modeling of Waiting Time Distribution in Kinetic States of Kinesin Nanomachine

Research paper thumbnail of Content based recommendation for HBB TV based on bayes conditional probability for multiple variables approach

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015

Research paper thumbnail of Measuring correlation between microarray time-series data using dominant spectral component

Proceedings of the Second Conference on Asia Pacific Bioinformatics Volume 29, 2004

Research paper thumbnail of Accurate Partial Volume Estimation of MR Brain Tissues

Research paper thumbnail of Microarray Image Analysis and Spot Segmentation

Research paper thumbnail of Reliable Detection of Short Periodic Gene Expression Time Series Profiles in DNA Microarray Data

2009 Ieee International Conference on Systems Man and Cybernetics, Oct 1, 2009

Research paper thumbnail of General Retinal Vessel Segmentation UsingRegularization-Based Multiconcavity Modeling

Research paper thumbnail of Recent Patents on Biclustering Algorithms for Gene Expression Data Analysis

Research paper thumbnail of Supp1 pfalcipuram ranking

ABSTRACT Please cite the following paper if you use this resource: ******************************... more ABSTRACT Please cite the following paper if you use this resource: ***************************************************************************************** A.W.C. Liew, J. Xian, S. Wu, D. Smith, and H. Yan, "Spectral Estimation in Unevenly Sampled Space of Periodically Expressed Microarray Time Series Data", BMC Bioinformatics, 8:137, 24 April 2007 *****************************************************************************************

Research paper thumbnail of Visual Speech Recognition: Lip Segmentation and Mapping

Research paper thumbnail of Missing value imputation for gene expression data: computational techniques to recover missing datafrom available information

Research paper thumbnail of Human Face Animation Based on Video Analysis, with Applications to Mobile Entertainment

Research paper thumbnail of Data Mining for Bioinformatics

Research paper thumbnail of Image Compression Concepts Overview

Research paper thumbnail of Content-Based Image Retrieval

Research paper thumbnail of Supp2 yeast ranking

Please cite the following paper if you use this resource: ***************************************... more Please cite the following paper if you use this resource: ***************************************************************************************** A.W.C. Liew, J. Xian, S. Wu, D. Smith, and H. Yan, "Spectral Estimation in Unevenly Sampled Space of Periodically Expressed Microarray Time Series Data", BMC Bioinformatics, 8:137, 24 April 2007 *****************************************************************************************

Research paper thumbnail of A novel OPTOC-based clustering algorithm for gene expression data analysis

Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint, 2003

Research paper thumbnail of Segmentation and Recognition of Multi-Model Photo Event

Neurocomputing, 2015

ABSTRACT Photograph becomes more and more convenient with the rapid growing of smart phones, whic... more ABSTRACT Photograph becomes more and more convenient with the rapid growing of smart phones, which makes photo become one of the most widely used social media. In this paper, we have proposed a segmentation and recognition method for multi-model photo event to help users organize and manage their increasing photo collections. Generative model of photo event is built by analyzing time, location, camera parameters and visual content of photos. Expectation-Maximization (EM) learning algorithm is applied to discover the best parameters of the proposed generative model. With the defined model, each photo is categorized into the corresponding event by calculating the maximum posteriori probability. The representativeness of an event is a photo collage constructed by selecting a set of representative photos from the corresponding event. The proposed method is characterized by the following properties: 1) unlike most of the existing photo event segmentation methods, the location of photos is treated as a key feature, 2) the representativeness of an event is a picture collage instead of a single photo, which is not only informative but also very appealing. The experimental results show that the proposed method is effective and efficient on the photo collections from three experienced smart phone users.

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