2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)最新文献

Rare Diseases clustering based on structural regularities at the gene structure 基于基因结构规律的罕见病聚类

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-12-17 DOI: 10.1109/BIBM.2015.7359961

Fabian Tobar-Tosse, Eliana Ocampo-Toro, Pedro M. Hernandez, A. Zuniga, Sebastian Florido-Sarria, Paula M. Hurtado

{"title":"Rare Diseases clustering based on structural regularities at the gene structure","authors":"Fabian Tobar-Tosse, Eliana Ocampo-Toro, Pedro M. Hernandez, A. Zuniga, Sebastian Florido-Sarria, Paula M. Hurtado","doi":"10.1109/BIBM.2015.7359961","DOIUrl":"https://doi.org/10.1109/BIBM.2015.7359961","url":null,"abstract":"Rare Diseases (RDs) are conditions with a high spectrum of genetic origins, whose phenotypic impact could define specific metabolic disorders or complex congenital anomalies. Accordingly, It is possible to propose at the point of view of the structural-genomics, that RDs define critical changes at the genome structure, which affect the cells functionality but not its viability. Herein, we present a bioinformatics approach for the identification of regularities among RDs related genes, which include the exploration of these genes at the map of the human genome reference, and its structural description considering the promoter regions. This approach allows us to identify structural regularities among RD genes, mainly related with the promoter regions, where the organization of genomic elements like CpG islands, and short repeats, allows an informative RDs clustering; that's mean nodes with functional and phenotypic meaning. For example, we present common regularities among RDs genes, which functionally are related to an immunological impact, and phenotypically with related syndromes: hyperimmunoglobulin E syndrome, Hyperimmunoglobulin E-recurrent infection syndrome, Job syndrome, and others. Based on our findings, we present an approximation for an integrative description of RDs, based on a basic structural-genomic overview.","PeriodicalId":186217,"journal":{"name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133648486","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}

引用次数: 0

Cross-validation of data in SAXS and cryo-EM 交叉验证SAXS和cryo-EM数据

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359856

B. Afsari, J. S. Kim, G. Chirikjian

引用次数: 2

Computing transition paths in multiple-basin proteins with a probabilistic roadmap algorithm guided by structure data 基于结构数据的概率路线图算法计算多盆蛋白的迁移路径

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359652

T. Maximova, E. Plaku, Amarda Shehu

{"title":"Computing transition paths in multiple-basin proteins with a probabilistic roadmap algorithm guided by structure data","authors":"T. Maximova, E. Plaku, Amarda Shehu","doi":"10.1109/BIBM.2015.7359652","DOIUrl":"https://doi.org/10.1109/BIBM.2015.7359652","url":null,"abstract":"Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal scales. In this paper we present a novel, sampling-based algorithm to compute transition paths. The algorithm exploits two main ideas. First, it leverages known structures to initialize its search and define a reduced conformation space for rapid sampling. This is key to address the insufficient sampling issue suffered by sampling-based algorithms. Second, the algorithm embeds samples in a nearest-neighbor graph where transition paths can be efficiently computed via queries. The algorithm adapts the probabilistic roadmap framework that is popular in robot motion planning. In addition to efficiently computing lowest-cost paths between any given structures, the algorithm allows investigating hypotheses regarding the order of experimentally-known structures in a transition event. This novel contribution is likely to open up new venues of research. Detailed analysis is presented on multiple-basin proteins of relevance to human disease. Multiscaling and the AMBER ff12SB force field are used to obtain energetically-credible paths at atomistic detail.","PeriodicalId":186217,"journal":{"name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121377684","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}

引用次数: 14

Implicit knowledge discovery in biomedical ontologies: Computing interesting relatednesses 生物医学本体中的隐性知识发现:计算有趣的相关性

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359734

Tian Bai, L. Gong, C. Kulikowski, Lan Huang

引用次数: 2

Bo's abdominal acupuncture mitigate post-stroke fatigue: A clinical center retrospective analysis 博氏腹针减轻脑卒中后疲劳:临床中心回顾性分析

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359931

Ruihuan Pan, Mingfeng He, Lechang Zhan, Zhen Huang, Jie Zhan, Hongxia Chen

{"title":"Bo's abdominal acupuncture mitigate post-stroke fatigue: A clinical center retrospective analysis","authors":"Ruihuan Pan, Mingfeng He, Lechang Zhan, Zhen Huang, Jie Zhan, Hongxia Chen","doi":"10.1109/BIBM.2015.7359931","DOIUrl":"https://doi.org/10.1109/BIBM.2015.7359931","url":null,"abstract":"Backgrounds: Post-stroke fatigue is a common and devastating malady of post-stroke patients. Bo's abdominal acupuncture is an effective therapeutic tool of Chinese medicine and widely used in practice in China. In this clinical study, we evaluated the therapeutic efficacy and safety of Bo's abdominal acupuncture for post-stroke fatigue. Methods: sixty participants with post-stroke fatigue were recruited and randomized to observational and acupuncture groups. The patients of acupuncture group were treated with Bo's abdominal acupuncture and rehabilitation exercise. The patients of observational group were treated with rehabilitation exercise. Two scoring systems, such as fatigue severity scale and stroke-specific quality of life scale, were used to analyze the therapeutic efficacy and safety of Bo's abdominal acupuncture, administered before and after treatment. Results: After four weeks, the patients with acupuncture displayed milder post-stroke fatigue in comparison with patients without acupuncture. Conclusion: Bo's abdominal acupuncture and rehabilitation exercise markedly mitigate post-stroke fatigue.","PeriodicalId":186217,"journal":{"name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122399570","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}

引用次数: 3

Protein-protein interaction extraction based on actively transfer learning 基于主动迁移学习的蛋白质-蛋白质相互作用提取

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359936

Lishuang Li, Jieqiong Zheng, Dingxin Song, Rui Guo, Degen Huang

引用次数: 0

Cell nuclei segmentation in glioma histopathology images with color decomposition based active contours 基于颜色分解的神经胶质瘤组织病理图像的细胞核分割

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359944

V. B. Surya Prasath, Kiichi Fukuma, B. Aronow, H. Kawanaka

引用次数: 10

Understanding heterogeneity in pregnancy-associated breast cancer 了解妊娠相关乳腺癌的异质性

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359851

T. Nair

引用次数: 0

Design of a real-time morphology-based anomaly detection method from ECG streams 基于形态学的实时心电异常检测方法的设计

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359793

D. Ngo, B. Veeravalli

引用次数: 9

HPMA: High-performance metagenomic alignment tool, on a large-scale GPU cluster HPMA:高性能宏基因组比对工具，基于大规模GPU集群

2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Pub Date : 2015-11-09 DOI: 10.1109/BIBM.2015.7359757

I. Savran, J. Rose

{"title":"HPMA: High-performance metagenomic alignment tool, on a large-scale GPU cluster","authors":"I. Savran, J. Rose","doi":"10.1109/BIBM.2015.7359757","DOIUrl":"https://doi.org/10.1109/BIBM.2015.7359757","url":null,"abstract":"In this paper, we present HPMA, a graphics processing unit (GPU) accelerated meta-genome sequence alignment algorithm for a collection of DNA sequences. This algorithm supports all-to-all pairwise local alignment on NVIDIA GPUs. HPMA builds on an GPU alignment algorithm that we developed earlier with the addition of a filter module. We designed and developed this new kernel function based on the suffix array data structure. The filter module improves performance by identifying a subset of sequences which meet a user-defined similarity threshold and should be considered for alignment. HPMA has the ability to balance the workload between CPU and GPU. HPMA allows us to preprocess massively large metagenomes in a reasonable amount of time in response to increasing speed of NGS sequencers. The performance of HPMA has been evaluated on a cluster of Kepler-based Tesla K20 GPUs using a variety of short DNA sequence datasets. We evaluate HPMA thoroughly with four test datasets. The first two test sets are comprised of 10 simulated datasets where read length varies from 72 to 750 base-pairs. The third test set is designed to allow a comparison with published results for GSWABE, a competing GPU alignment tool. The fourth test set is an actual metagenome of over 2 million sequences with an average length of 270 bp. We utilized a cluster of NVIDIA-K20 GPUs in the Stampede supercomputer at the Texas Advanced Computing Center (Austin, TX, USA). When running on a cluster of 10 NVIDIA K20 GPUs, HPMA is able to align 2 million simulated metagenome sequences of length 300 bp in 160 seconds. In the case of real metagenomic data, HPMA is able to align 2,038,516 sequences with an average length of 270 bp in 60 seconds.","PeriodicalId":186217,"journal":{"name":"2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128475982","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}

引用次数: 0