Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470264
Sagar Patel, H. Panchal, K. Anjaria
A multiple sequence alignment (MSA) is a sequence alignment of three or more biological sequences, generally for Protein. MSA has wide range of applications and to cite few of them such as phylogenetic analysis, protein pattern identification, protein domain identification, prediction of protein structure, structural similarity of amino acids and to get evolutionary similarity. ClustalW2 is a general purpose global multiple sequence alignment program for proteins. It produces biologically meaningful multiple sequence alignments of divergent sequences. The output from ClustalW2 shows the best match for the selected sequences and lines up them in such a way that the identities, similarities and differences can be easily understood. Evolutionary relationships can be seen by creating Cladograms or Phylograms. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. In this paper, protein sequences of few legume species from UNIPROT database were taken and focused on MSA for protein sequences for these tree species of family Leguminosae, where ClustalW2 tool have used to generate biological data. The results are discussed with the help of Cladograms and Phylograms for selected tree species.
{"title":"Phylogenetic analysis of some leguminous trees using CLUSTALW2 bioinformatics tool","authors":"Sagar Patel, H. Panchal, K. Anjaria","doi":"10.1109/BIBMW.2012.6470264","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470264","url":null,"abstract":"A multiple sequence alignment (MSA) is a sequence alignment of three or more biological sequences, generally for Protein. MSA has wide range of applications and to cite few of them such as phylogenetic analysis, protein pattern identification, protein domain identification, prediction of protein structure, structural similarity of amino acids and to get evolutionary similarity. ClustalW2 is a general purpose global multiple sequence alignment program for proteins. It produces biologically meaningful multiple sequence alignments of divergent sequences. The output from ClustalW2 shows the best match for the selected sequences and lines up them in such a way that the identities, similarities and differences can be easily understood. Evolutionary relationships can be seen by creating Cladograms or Phylograms. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. In this paper, protein sequences of few legume species from UNIPROT database were taken and focused on MSA for protein sequences for these tree species of family Leguminosae, where ClustalW2 tool have used to generate biological data. The results are discussed with the help of Cladograms and Phylograms for selected tree species.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"57 1","pages":"917-921"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91325771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470295
J. B. Brown, S. Niijima, A. Shiraishi, M. Nakatsui, Y. Okuno
Chemogenomics has emerged as an interdisciplinary field that aims to ultimately identify all possible ligands of all target families in a systematic manner. An ever-increasing need to explore the vast space of both ligands and targets has recently triggered the development of novel computational techniques for chemogenomics, which have the potential to play a crucial role in drug discovery. Among others, a kernel-based machine learning approach has attracted increasing attention. Here, we explore the applicability of several ligand-target kernels by extensively evaluating the prediction performance of ligand-target interactions on five target families, and reveal how different combinations of ligand kernels and protein kernels affect the performance and also how the performance varies between the target families.
{"title":"Chemogenomic approach to comprehensive predictions of ligand-target interactions: A comparative study","authors":"J. B. Brown, S. Niijima, A. Shiraishi, M. Nakatsui, Y. Okuno","doi":"10.1109/BIBMW.2012.6470295","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470295","url":null,"abstract":"Chemogenomics has emerged as an interdisciplinary field that aims to ultimately identify all possible ligands of all target families in a systematic manner. An ever-increasing need to explore the vast space of both ligands and targets has recently triggered the development of novel computational techniques for chemogenomics, which have the potential to play a crucial role in drug discovery. Among others, a kernel-based machine learning approach has attracted increasing attention. Here, we explore the applicability of several ligand-target kernels by extensively evaluating the prediction performance of ligand-target interactions on five target families, and reveal how different combinations of ligand kernels and protein kernels affect the performance and also how the performance varies between the target families.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"36 1","pages":"136-142"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90060651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470326
Masood Zamani, S. C. Kremer
In this study, we evaluate the performance of a protein secondary structure prediction model using a new amino acid "codon" encoding inspired by genetic codon mappings. The dimensionality of the binary codon encoding is less than that of an orthogonal encoding which requires less computations. Protein secondary structure prediction is an important step for machine learning techniques ultimately applied for protein 3D structure prediction. In the proposed model, one-stage binary support vector machines are employed, and the efficiency of the codon encoding to that of a commonly used orthogonal encoding are compared without incorporating protein evolutionary and structural information for an unbiased comparison. The performance of the classification model is measured according to Q3 and segment overlap (SOV) scores. The scores are compared with those of the prediction methods using an orthogonal encoding and protein sequence profiles. The experimental results indicate higher prediction accuracy based on Q3 SOV scores when sequence profiles are not used. Also, the relative classification scores of the proposed method are comparable with the methods incorporating protein global and evolutionary information. The experimental result implies the encoding scheme is able to integrate the evolutionary information into the prediction model since the encoding is based on genetic codon mappings which are the building blocks of amino acid formations at the primary level of biological processes. The codon encoding is worthwhile to be investigated using more complex learning architectures with the profiles and structural properties of proteins.
{"title":"Protein secondary structure prediction using support vector machines and a codon encoding scheme","authors":"Masood Zamani, S. C. Kremer","doi":"10.1109/BIBMW.2012.6470326","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470326","url":null,"abstract":"In this study, we evaluate the performance of a protein secondary structure prediction model using a new amino acid \"codon\" encoding inspired by genetic codon mappings. The dimensionality of the binary codon encoding is less than that of an orthogonal encoding which requires less computations. Protein secondary structure prediction is an important step for machine learning techniques ultimately applied for protein 3D structure prediction. In the proposed model, one-stage binary support vector machines are employed, and the efficiency of the codon encoding to that of a commonly used orthogonal encoding are compared without incorporating protein evolutionary and structural information for an unbiased comparison. The performance of the classification model is measured according to Q3 and segment overlap (SOV) scores. The scores are compared with those of the prediction methods using an orthogonal encoding and protein sequence profiles. The experimental results indicate higher prediction accuracy based on Q3 SOV scores when sequence profiles are not used. Also, the relative classification scores of the proposed method are comparable with the methods incorporating protein global and evolutionary information. The experimental result implies the encoding scheme is able to integrate the evolutionary information into the prediction model since the encoding is based on genetic codon mappings which are the building blocks of amino acid formations at the primary level of biological processes. The codon encoding is worthwhile to be investigated using more complex learning architectures with the profiles and structural properties of proteins.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"88 1","pages":"22-27"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90592923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470312
Chen Geng, Jian Yang, Tong Li, Yongtian Wang
Currently, photographic film is the most commonly used medium for viewing medical images in hospitals. However, as digitalized medical images need to be printed on photographic film first, such kind of viewing pattern has an extremely limited use A homogeneous white light source is also needed to observe the anatomic structure clearly. Such observation pattern is very limited to the circumstances in which it is used In this paper, a novel interactive non-contact system is developed to observe multimodal medical images. For this system, a series of gestures is defined, and a depth sensor is used to capture the speckle pattern of infrared laser, which irradiates to the person in front of the system By analyzing the morphologic atlas of the depth photo, the 3-D structure and the motion of the captured image can be obtained in real time. Then, all kinds of operations on medical images, including transformation, contrast adjustment, volume rendering, can be achieved through different gesture regulations. The system developed realizes flexible observation of medical images using digitalized images directly, which greatly reduces expenses for the clinical diagnosis. The system does not need any contact with the medium. Therefore, it can be utilized by doctors doing clinical surgery.
{"title":"A novel non-contact interactive medical image viewing system","authors":"Chen Geng, Jian Yang, Tong Li, Yongtian Wang","doi":"10.1109/BIBMW.2012.6470312","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470312","url":null,"abstract":"Currently, photographic film is the most commonly used medium for viewing medical images in hospitals. However, as digitalized medical images need to be printed on photographic film first, such kind of viewing pattern has an extremely limited use A homogeneous white light source is also needed to observe the anatomic structure clearly. Such observation pattern is very limited to the circumstances in which it is used In this paper, a novel interactive non-contact system is developed to observe multimodal medical images. For this system, a series of gestures is defined, and a depth sensor is used to capture the speckle pattern of infrared laser, which irradiates to the person in front of the system By analyzing the morphologic atlas of the depth photo, the 3-D structure and the motion of the captured image can be obtained in real time. Then, all kinds of operations on medical images, including transformation, contrast adjustment, volume rendering, can be achieved through different gesture regulations. The system developed realizes flexible observation of medical images using digitalized images directly, which greatly reduces expenses for the clinical diagnosis. The system does not need any contact with the medium. Therefore, it can be utilized by doctors doing clinical surgery.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"157 1","pages":"254-259"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78588356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470355
Benjie Qi, Qingfeng Luo, Mingzhi Wan
With needle scalpel, we have treated 145 cases of traumatic ankylosis, including 35 cases of knees, 32 cases of ankles, 38 cases of shoulders, 40 cases of elbows. And we find the treatment is easy to operate, with few side effects, but significant effect.
{"title":"Clinical curative effect of needle scalpel for traumatic ankylosis","authors":"Benjie Qi, Qingfeng Luo, Mingzhi Wan","doi":"10.1109/BIBMW.2012.6470355","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470355","url":null,"abstract":"With needle scalpel, we have treated 145 cases of traumatic ankylosis, including 35 cases of knees, 32 cases of ankles, 38 cases of shoulders, 40 cases of elbows. And we find the treatment is easy to operate, with few side effects, but significant effect.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"23 1","pages":"435-436"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85582969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced technologies are producing large-scale protein-protein interaction data at an ever increasing pace. Finding protein-protein interaction complexes from large PPI networks is a fundamental problem in bioinformatics. As a group of core proteins which interacts with other more proteins, hub proteins play a key role in protein complex and life activity. In this paper, we propose a novel topological model, HP*-complex, which defines the hub proteins of protein complex and extends to encompass the neighborhood of the hub proteins, for the initial structure of protein complexes. An algorithm based on the new topological model, called HPCMiner, is developed for identifying protein complexes from large PPI networks. The experiment results on real dataset show that our proposed algorithm detects many complexes having special biological significance. The results from a study on synthetic data sets demonstrate that the HPCMiner algorithm scales well with respect to data set size.
{"title":"Mining hub-based protein complexes in massive biological networks","authors":"Zhijie Lin, Yan Chen, Shiwei Wu, Yun Xiong, Yangyong Zhu, Guangyong Zheng","doi":"10.1109/BIBMW.2012.6470299","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470299","url":null,"abstract":"Advanced technologies are producing large-scale protein-protein interaction data at an ever increasing pace. Finding protein-protein interaction complexes from large PPI networks is a fundamental problem in bioinformatics. As a group of core proteins which interacts with other more proteins, hub proteins play a key role in protein complex and life activity. In this paper, we propose a novel topological model, HP*-complex, which defines the hub proteins of protein complex and extends to encompass the neighborhood of the hub proteins, for the initial structure of protein complexes. An algorithm based on the new topological model, called HPCMiner, is developed for identifying protein complexes from large PPI networks. The experiment results on real dataset show that our proposed algorithm detects many complexes having special biological significance. The results from a study on synthetic data sets demonstrate that the HPCMiner algorithm scales well with respect to data set size.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"58 1","pages":"166-173"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84516476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470347
Jian Li, D. Guo, Liu Jinwen, Jian-ke Pan, Lufeng Huang, Jun Liu
Liu Jinwen is Professor of Guangzhou University of Chinese Medicine of Traditional Chinese medicine bone-setting professional doctoral tutor and postdoctoral supervisor, one of the veteran TCM experts of Guangdong Province. Former director of the department of orthopedics of Guangdong Provencal Hospital of TCM. Over the past 50 years, Professor Liu Jensen has been engaged in research on prevention and treatment of bone and joint degenerative diseases of TCM and expert in theory of TCM research. He always emphasized on the prevention and treatment of diseases in clinical practice to follow the overall concept, principle of correspondence between man and universe and treatment based on syndrome differentiation. Knowledge about osteoarthritis of the knee, in his view, is not just a local issue, but overall to reflect local, and stresses therefore that on the treatment measures must be taken to proceed from the overall, good results can be achieved, overall is strengthening healthy Qi, conditioning of yin and Yang to restore homeostasis.
{"title":"Prof. Liu Jinwen's experience on treating knee osteoarthritis","authors":"Jian Li, D. Guo, Liu Jinwen, Jian-ke Pan, Lufeng Huang, Jun Liu","doi":"10.1109/BIBMW.2012.6470347","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470347","url":null,"abstract":"Liu Jinwen is Professor of Guangzhou University of Chinese Medicine of Traditional Chinese medicine bone-setting professional doctoral tutor and postdoctoral supervisor, one of the veteran TCM experts of Guangdong Province. Former director of the department of orthopedics of Guangdong Provencal Hospital of TCM. Over the past 50 years, Professor Liu Jensen has been engaged in research on prevention and treatment of bone and joint degenerative diseases of TCM and expert in theory of TCM research. He always emphasized on the prevention and treatment of diseases in clinical practice to follow the overall concept, principle of correspondence between man and universe and treatment based on syndrome differentiation. Knowledge about osteoarthritis of the knee, in his view, is not just a local issue, but overall to reflect local, and stresses therefore that on the treatment measures must be taken to proceed from the overall, good results can be achieved, overall is strengthening healthy Qi, conditioning of yin and Yang to restore homeostasis.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"1 1","pages":"402-405"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90906109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470364
Changeai Xie, Nipeng Lin, Jiaxin Zhou, Zhiqi Fan, W. Fu
This article introduces the clinical experience of three-step ladder therapy of Professor Fu on gouty arthritis. In accordance with the overall syndrome and Meridian dialectical combined with the disease clinical feature, Professor Fu cures gouty arthritis from the start of pain. The first step is the application of eye acupuncture and body acupuncture in order to rapidly relieve the patient's pain; The second step is the application of moxibustion, fire needle and blood-letting puncture to enhance the efficacy; The third step is the buried intradermal needle to solidate long-term efficacy. Professor Fu's three-step ladder therapy on gouty arthritis has achieved the exact effect and significantly guided in clinical practice.
{"title":"The experimental introduction of professor Fu's three-step therapy on gouty arthritis","authors":"Changeai Xie, Nipeng Lin, Jiaxin Zhou, Zhiqi Fan, W. Fu","doi":"10.1109/BIBMW.2012.6470364","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470364","url":null,"abstract":"This article introduces the clinical experience of three-step ladder therapy of Professor Fu on gouty arthritis. In accordance with the overall syndrome and Meridian dialectical combined with the disease clinical feature, Professor Fu cures gouty arthritis from the start of pain. The first step is the application of eye acupuncture and body acupuncture in order to rapidly relieve the patient's pain; The second step is the application of moxibustion, fire needle and blood-letting puncture to enhance the efficacy; The third step is the buried intradermal needle to solidate long-term efficacy. Professor Fu's three-step ladder therapy on gouty arthritis has achieved the exact effect and significantly guided in clinical practice.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"1 1","pages":"463-465"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90452804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470200
Jasjit K. Banwait, H. Ali, D. Bastola
MicroRNAs are small (approx. 22nt) noncoding RNAs that regulate gene expression by either degrading messenger-RNA (mRNA) that has already been transcribed or by repressing the translation of mRNA. This mechanism of gene regulation by binding of the miRNA to 3-prime-UTR of target mRNAs has been recently discovered and sequence-specific post-transcriptional gene regulation process affects large set of genes involved in number of biological pathways. Mapping of 7nt long miRNAseed sequence to the target gene has been a standard way of predicting miRNA targets. In this study, we have generated a profile-based filter to increase the specificity of human miRNA-mRNA relationship thereby enriching true-positive miRNA target sitesin humans based on sequence information.
{"title":"Enriching miRNA binding site specificity with sequence profile based filtering of 3'-UTR region of mRNA","authors":"Jasjit K. Banwait, H. Ali, D. Bastola","doi":"10.1109/BIBMW.2012.6470200","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470200","url":null,"abstract":"MicroRNAs are small (approx. 22nt) noncoding RNAs that regulate gene expression by either degrading messenger-RNA (mRNA) that has already been transcribed or by repressing the translation of mRNA. This mechanism of gene regulation by binding of the miRNA to 3-prime-UTR of target mRNAs has been recently discovered and sequence-specific post-transcriptional gene regulation process affects large set of genes involved in number of biological pathways. Mapping of 7nt long miRNAseed sequence to the target gene has been a standard way of predicting miRNA targets. In this study, we have generated a profile-based filter to increase the specificity of human miRNA-mRNA relationship thereby enriching true-positive miRNA target sitesin humans based on sequence information.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"1 1","pages":"558-563"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88876166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-04DOI: 10.1109/BIBMW.2012.6470223
Julia D. Warnke-Sommer, H. Ali
Next generation sequencing has quickly emerged as the most exciting yet challenging computational problem in Bioinformatics. Current sequencing technologies are capable of producing several hundreds of thousands to several millions of short sequence reads in a single run. However, current methods for managing, storing, and processing the produced reads remain for the most part simple and lack the complexity needed to model the produced reads efficiently and assemble them correctly. These reads are produced at a high coverage of the original target sequence such that many reads overlap. The overlap relationships are used to align and merge reads into contiguous sequences called contigs. In this paper, we present an overlap graph coarsening scheme for modeling reads and their overlap relationships. Our approach is different from previous read analysis and assembly methods that use a single graph to model read overlap relationships. Instead, we use a series of graphs with different granularities of information to represent the complex read overlap relationships. We present a new graph coarsening algorithm for clustering a simulated metagenomics dataset at various levels of granularity. We also use the proposed graph coarsening scheme along with graph traversal algorithms to find a labeling of the overlap graph that allows for the efficient organization of nodes within the graph data structure.
{"title":"An efficient overlap graph coarsening approach for modeling short reads","authors":"Julia D. Warnke-Sommer, H. Ali","doi":"10.1109/BIBMW.2012.6470223","DOIUrl":"https://doi.org/10.1109/BIBMW.2012.6470223","url":null,"abstract":"Next generation sequencing has quickly emerged as the most exciting yet challenging computational problem in Bioinformatics. Current sequencing technologies are capable of producing several hundreds of thousands to several millions of short sequence reads in a single run. However, current methods for managing, storing, and processing the produced reads remain for the most part simple and lack the complexity needed to model the produced reads efficiently and assemble them correctly. These reads are produced at a high coverage of the original target sequence such that many reads overlap. The overlap relationships are used to align and merge reads into contiguous sequences called contigs. In this paper, we present an overlap graph coarsening scheme for modeling reads and their overlap relationships. Our approach is different from previous read analysis and assembly methods that use a single graph to model read overlap relationships. Instead, we use a series of graphs with different granularities of information to represent the complex read overlap relationships. We present a new graph coarsening algorithm for clustering a simulated metagenomics dataset at various levels of granularity. We also use the proposed graph coarsening scheme along with graph traversal algorithms to find a labeling of the overlap graph that allows for the efficient organization of nodes within the graph data structure.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":"6 1","pages":"704-711"},"PeriodicalIF":0.0,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72920343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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