The Experts below are selected from a list of 119160 Experts worldwide ranked by ideXlab platform
John R Yates - One of the best experts on this subject based on the ideXlab platform.
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A ...
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A modified version of the de novo identification algorithm PILOT, is utilized to construct accurate de novo peptide sequences. A modified version of the Local Database search tool FASTA is used to query these de novo predictions against the nonredundant protein Database to resolve any low-confidence amino acids in the candidate sequences. The computational burden associated with performing several alignments is alleviated with the use of distributive computing. Extensive computational studies are presented for this new hybrid methodology, as well as comparisons with MASCOT for a set of 38 quadrupole time-of-flight (QTOF) and 380 OrbiTrap tandem mass spectra. The results for our proposed hybrid method for the OrbiTrap spectra are also compared with a modified version of PepNovo, which was trained for use on high-precision tandem mass spectra, and the tag-based method InsPecT. The de novo sequences of PILOT and PepNovo are also searched against the nonredundant protein Database using CIDentify to compare with the alignments achieved by our modifications of FASTA. The comparative studies demonstrate the excellent peptide identification accuracy gained from combining the strengths of our de novo method, which is based on integer linear optimization, and Database driven search methods.
Meysam Tavakoli - One of the best experts on this subject based on the ideXlab platform.
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a complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy
arXiv: Medical Physics, 2019Co-Authors: Meysam Tavakoli, Reza Pourreza Shahri, Hamid Reza Pourreza, Alireza Mehdizadeh, Touka Banaee, Mohammad Hosein Bahreini ToosiAbstract:Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography (FA) fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated reported on three different retinal images Databases, the Mashhad Database with 120 FA fundus images, Second Local Database from Tehran with 50 FA retinal images and a part of Retinopathy Online Challenge (ROC) Database with 22 images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad Database and 100% and 70% for the Second Local Database respectively.
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a complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy
Pattern Recognition, 2013Co-Authors: Meysam Tavakoli, Reza Pourreza Shahri, Hamid Reza Pourreza, Alireza Mehdizadeh, Touka Banaee, Mohammad Hosein Bahreini ToosiAbstract:Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography (FA) fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated on three different retinal images Databases, the Mashhad Database with 120 FA fundus images, Second Local Database from Tehran with 50 FA retinal images and a part of Retinopathy Online Challenge (ROC) Database with 22 images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad Database and 100% and 70% for the Second Local Database respectively.
Peter A Dimaggio - One of the best experts on this subject based on the ideXlab platform.
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A ...
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A modified version of the de novo identification algorithm PILOT, is utilized to construct accurate de novo peptide sequences. A modified version of the Local Database search tool FASTA is used to query these de novo predictions against the nonredundant protein Database to resolve any low-confidence amino acids in the candidate sequences. The computational burden associated with performing several alignments is alleviated with the use of distributive computing. Extensive computational studies are presented for this new hybrid methodology, as well as comparisons with MASCOT for a set of 38 quadrupole time-of-flight (QTOF) and 380 OrbiTrap tandem mass spectra. The results for our proposed hybrid method for the OrbiTrap spectra are also compared with a modified version of PepNovo, which was trained for use on high-precision tandem mass spectra, and the tag-based method InsPecT. The de novo sequences of PILOT and PepNovo are also searched against the nonredundant protein Database using CIDentify to compare with the alignments achieved by our modifications of FASTA. The comparative studies demonstrate the excellent peptide identification accuracy gained from combining the strengths of our de novo method, which is based on integer linear optimization, and Database driven search methods.
Christodoulos A Floudas - One of the best experts on this subject based on the ideXlab platform.
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A ...
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a hybrid method for peptide identification using integer linear optimization Local Database search and quadrupole time of flight or orbitrap tandem mass spectrometry
Journal of Proteome Research, 2008Co-Authors: Peter A Dimaggio, Christodoulos A Floudas, John R YatesAbstract:A novel hybrid methodology for the automated identification of peptides via de novo integer linear optimization, Local Database search, and tandem mass spectrometry is presented in this article. A modified version of the de novo identification algorithm PILOT, is utilized to construct accurate de novo peptide sequences. A modified version of the Local Database search tool FASTA is used to query these de novo predictions against the nonredundant protein Database to resolve any low-confidence amino acids in the candidate sequences. The computational burden associated with performing several alignments is alleviated with the use of distributive computing. Extensive computational studies are presented for this new hybrid methodology, as well as comparisons with MASCOT for a set of 38 quadrupole time-of-flight (QTOF) and 380 OrbiTrap tandem mass spectra. The results for our proposed hybrid method for the OrbiTrap spectra are also compared with a modified version of PepNovo, which was trained for use on high-precision tandem mass spectra, and the tag-based method InsPecT. The de novo sequences of PILOT and PepNovo are also searched against the nonredundant protein Database using CIDentify to compare with the alignments achieved by our modifications of FASTA. The comparative studies demonstrate the excellent peptide identification accuracy gained from combining the strengths of our de novo method, which is based on integer linear optimization, and Database driven search methods.
Mohammad Hosein Bahreini Toosi - One of the best experts on this subject based on the ideXlab platform.
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a complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy
arXiv: Medical Physics, 2019Co-Authors: Meysam Tavakoli, Reza Pourreza Shahri, Hamid Reza Pourreza, Alireza Mehdizadeh, Touka Banaee, Mohammad Hosein Bahreini ToosiAbstract:Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography (FA) fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated reported on three different retinal images Databases, the Mashhad Database with 120 FA fundus images, Second Local Database from Tehran with 50 FA retinal images and a part of Retinopathy Online Challenge (ROC) Database with 22 images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad Database and 100% and 70% for the Second Local Database respectively.
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a complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy
Pattern Recognition, 2013Co-Authors: Meysam Tavakoli, Reza Pourreza Shahri, Hamid Reza Pourreza, Alireza Mehdizadeh, Touka Banaee, Mohammad Hosein Bahreini ToosiAbstract:Early detection of microaneurysms (MAs), the first sign of Diabetic Retinopathy (DR), is an essential first step in automated detection of DR to prevent vision loss and blindness. This study presents a novel and different algorithm for automatic detection of MAs in fluorescein angiography (FA) fundus images, based on Radon transform (RT) and multi-overlapping windows. This project addresses a novel method, in detection of retinal land marks and lesions to diagnose the DR. At the first step, optic nerve head (ONH) was detected and masked. In preprocessing stage, top-hat transformation and averaging filter were applied to remove the background. In main processing section, firstly, we divided the whole preprocessed image into sub-images and then segmented and masked the vascular tree by applying RT in each sub-image. After detecting and masking retinal vessels and ONH, MAs were detected and numbered by using RT and appropriated thresholding. The results of the proposed method were evaluated on three different retinal images Databases, the Mashhad Database with 120 FA fundus images, Second Local Database from Tehran with 50 FA retinal images and a part of Retinopathy Online Challenge (ROC) Database with 22 images. Automated DR detection demonstrated a sensitivity and specificity of 94% and 75% for Mashhad Database and 100% and 70% for the Second Local Database respectively.