ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine最新文献_第3页

A Histogram-based Outlier Profile for Atomic Structures Derived from Cryo-Electron Microscopy. 基于直方图的异常值剖面图，用于从冷冻电子显微镜得出的原子结构。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2019-09-01 DOI: 10.1145/3307339.3343865

Lin Chen, Jing He

{"title":"A Histogram-based Outlier Profile for Atomic Structures Derived from Cryo-Electron Microscopy.","authors":"Lin Chen, Jing He","doi":"10.1145/3307339.3343865","DOIUrl":"10.1145/3307339.3343865","url":null,"abstract":"As more atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. We report findings after analyzing the change of cryo-EM structures in a comparison between those released by December 2016 and those released between 2017 and 2019. The cryo-EM models created from density maps with resolution better than 6 Å were divided into six data sets. A histogram-based outlier score (HBOS) was implemented and validation reports were collected from the Protein Data Bank. The results suggest that the overall quality of EM structures released after December 2016 is better than that of structures released before 2017. The conformation qualities of most residue types might have been improved, except for Leucine, Phenylalanine, and Serine in high-resolution datasets (higher than 4 Å). We observe that structures solved from 0-4 Å resolution density maps have an almost identical HBOS profile as that of structures derived from density maps with 4-6 Å resolution.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279010/pdf/nihms-1662219.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40507828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving Validity of Cause of Death on Death Certificates. 提高死亡证明书死因的有效性。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233581

Ryan A Hoffman, Janani Venugopalan, Li Qu, Hang Wu, May D Wang

{"title":"Improving Validity of Cause of Death on Death Certificates.","authors":"Ryan A Hoffman, Janani Venugopalan, Li Qu, Hang Wu, May D Wang","doi":"10.1145/3233547.3233581","DOIUrl":"10.1145/3233547.3233581","url":null,"abstract":"Accurate reporting of causes of death on death certificates is essential to formulate appropriate disease control, prevention and emergency response by national health-protection institutions such as Center for disease prevention and control (CDC). In this study, we utilize knowledge from publicly available expert-formulated rules for the cause of death to determine the extent of discordance in the death certificates in national mortality data with the expert knowledge base. We also report the most commonly occurring invalid causal pairs which physicians put in the death certificates. We use sequence rule mining to find patterns that are most frequent on death certificates and compare them with the rules from the expert knowledge based. Based on our results, 20.1% of the common patterns derived from entries into death certificates were discordant. The most probable causes of these discordance or invalid rules are missing steps and non-specific ICD-10 codes on the death certificates.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38067060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Using Combined Features to Analyze Atomic Structures Derived from Cryo-EM Density Maps. 利用组合特征分析从低温电镜密度图中得到的原子结构。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233709

Lin Chen, Jing He

{"title":"Using Combined Features to Analyze Atomic Structures Derived from Cryo-EM Density Maps.","authors":"Lin Chen, Jing He","doi":"10.1145/3233547.3233709","DOIUrl":"https://doi.org/10.1145/3233547.3233709","url":null,"abstract":"Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. Many atomic structures have been derived from cryo-EM density maps of about 3Å resolution. Side-chain conformations are well determined in density maps with super-resolutions such as 1-2Å. It is desirable to have a statistical method to detect anomalous side-chains without a super-resolution density map. In this study, we analyzed structures derived from X-ray density maps with higher than 1.5Å resolution and those from cryo-EM density maps with 2-4 Å and 4-6 Å resolutions respectively. We introduce a histogram-based outlier score (HBOS) for anomaly detection in protein models built from cryo-EM density maps. This method uses the statistics derived from X-ray dataset (<1.5Å) as the reference and combines five features involving the distal block distance, side-chain length, phi, psi, and first chi angle of the residue. Higher percentages of anomalies were observed in the cryo-EM models than in the super-resolution X-ray models. Lower percentages of anomalies were observed in cryo-EM models derived after January 2017 than those derived before 2017.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233709","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9869907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm. 基于邻域正则化三因子一类协同过滤算法的转录因子靶基因预测。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233551

Hansaim Lim, Lei Xie

{"title":"Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm.","authors":"Hansaim Lim, Lei Xie","doi":"10.1145/3233547.3233551","DOIUrl":"https://doi.org/10.1145/3233547.3233551","url":null,"abstract":"Identifying the target genes of transcription factors (TFs) is one of the key factors to understand transcriptional regulation. However, our understanding of genome-wide TF targeting profile is limited due to the cost of large scale experiments and intrinsic complexity. Thus, computational prediction methods are useful to predict the unobserved associations. Here, we developed a new one-class collaborative filtering algorithm tREMAP that is based on regularized, weighted nonnegative matrix tri-factorization. The algorithm predicts unobserved target genes for TFs using known gene-TF associations and protein-protein interaction network. Our benchmark study shows that tREMAP significantly outperforms its counterpart REMAP, a bi-factorization-based algorithm, for transcription factor target gene prediction in all four performance metrics AUC, MAP, MPR, and HLU. When evaluated by independent data sets, the prediction accuracy is 37.8% on the top 495 predicted associations, an enrichment factor of 4.19 compared with the random guess. Furthermore, many of the predicted novel associations by tREMAP are supported by evidence from literature. Although we only use canonical TF-target gene interaction data in this study, tREMAP can be directly applied to tissue-specific data sets. tREMAP provides a framework to integrate multiple omics data for the further improvement of TF target gene prediction. Thus, tREMAP is a potentially useful tool in studying gene regulatory networks. The benchmark data set and the source code of tREMAP are freely available at https://github.com/hansaimlim/REMAP/tree/master/TriFacREMAP.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233551","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37380671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Exploratory Studies Detecting Secondary Structures in Medium Resolution 3D Cryo-EM Images Using Deep Convolutional Neural Networks. 利用深度卷积神经网络检测中分辨率三维冷冻电镜图像中二级结构的探索性研究。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233704

Devin Haslam, Tao Zeng, Rongjian Li, Jing He

引用次数: 6

Neuroinformatics and Analysis of Connectomic Alterations Due to Cerebral Microhemorrhages in Geriatric Mild Neurotrauma. 老年轻度神经外伤脑微出血引起的神经信息学和连接组改变分析。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233598

Alexander S Maher, Kenneth A Rostowsky, Nahian F Chowdhury, Andrei Irimia

{"title":"Neuroinformatics and Analysis of Connectomic Alterations Due to Cerebral Microhemorrhages in Geriatric Mild Neurotrauma.","authors":"Alexander S Maher, Kenneth A Rostowsky, Nahian F Chowdhury, Andrei Irimia","doi":"10.1145/3233547.3233598","DOIUrl":"https://doi.org/10.1145/3233547.3233598","url":null,"abstract":"Connectomics alterations associated with subtle forms of cerebrovascular neuropathology-such as cerebral microbleeds (CMBs)-can result in substantial neurological and/or cognitive deficits in victims of traumatic brain injury (TBI). Quantifying CMB-related connectome changes in mild TBI (mTBI) patients requires ingenious neuroinformatics to integrate structural magnetic resonance imaging (sMRI) with diffusion-weighted imaging (DWI) for patient-tailored profiling while preserving the data scientist's ability to implement population studies. Such solutions, however, can assist the refinement of rehabilitation protocols and streamline large-scale analysis while accommodating the heterogeneity of mTBI. This study describes a pipeline for the multimodal integration of sMRI/DWI/DTI to quantify white matter (WM) neural network circuitry alterations associated with mTBI-related CMBs. The approach incorporates WM streamline matching, topology-compliant streamline prototyping and along-tract analysis within a unified framework. When applied to the analysis of neuroimaging data acquired from both mTBI and healthy control volunteers, the approach facilitates the identification of patient-specific CMB-related connectomic changes while incorporating the ability to perform group analyses. This pipeline for the identification and profiling of connectopathies can assist the adaptation of clinical rehabilitation protocols to patients' individual needs.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36902673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

ULTRA: A Model Based Tool to Detect Tandem Repeats. ULTRA:一种基于模型的串联重复序列检测工具

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233604

Daniel Olson, Travis Wheeler

{"title":"ULTRA: A Model Based Tool to Detect Tandem Repeats.","authors":"Daniel Olson, Travis Wheeler","doi":"10.1145/3233547.3233604","DOIUrl":"https://doi.org/10.1145/3233547.3233604","url":null,"abstract":"In biological sequences, tandem repeats consist of tens to hundreds of residues of a repeated pattern, such as atgatgatgatgatg ('atg' repeated), often the result of replication slippage. Over time, these repeats decay so that the original sharp pattern of repetition is somewhat obscured, but even degenerate repeats pose a problem for sequence annotation: when two sequences both contain shared patterns of similar repetition, the result can be a false signal of sequence homology. We describe an implementation of a new hidden Markov model for detecting tandem repeats that shows substantially improved sensitivity to labeling decayed repetitive regions, presents low and reliable false annotation rates across a wide range of sequence composition, and produces scores that follow a stable distribution. On typical genomic sequence, the time and memory requirements of the resulting tool (ULTRA) are competitive with the most heavily used tool for repeat masking (TRF). ULTRA is released under an open source license and lays the groundwork for inclusion of the model in sequence alignment tools and annotation pipelines.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37231821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Splice-Aware Multiple Sequence Alignment of Protein Isoforms. 蛋白质异构体的剪接感知多序列比对。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2018-08-01 DOI: 10.1145/3233547.3233592

Alex Nord, Kaitlin Carey, Peter Hornbeck, Travis Wheeler

{"title":"Splice-Aware Multiple Sequence Alignment of Protein Isoforms.","authors":"Alex Nord, Kaitlin Carey, Peter Hornbeck, Travis Wheeler","doi":"10.1145/3233547.3233592","DOIUrl":"10.1145/3233547.3233592","url":null,"abstract":"Multiple sequence alignment (MSA) is a classic problem in computational genomics. In typical use, MSA software is expected to align a collection of homologous genes, such as orthologs from multiple species or duplication-induced paralogs within a species. Recent focus on the importance of alternatively-spliced isoforms in disease and cell biology has highlighted the need to create MSAs that more effectively accommodate isoforms. MSAs are traditionally constructed using scoring criteria that prefer alignments with occasional mismatches over alignments with long gaps. Alternatively spliced protein isoforms effectively contain exon-length insertions or deletions (indels) relative to each other, and demand an alternative approach. Some improvements can be achieved by making indel penalties much smaller, but this is merely a patchwork solution. In this work we present Mirage, a novel MSA software package for the alignment of alternatively spliced protein isoforms. Mirage aligns isoforms to each other by first mapping each protein sequence to its encoding genomic sequence, and then aligning isoforms to one another based on the relative genomic coordinates of their constitutive codons. Mirage is highly effective at mapping proteins back to their encoding exons, and these protein-genome mappings lead to extremely accurate intra-species alignments; splice site information in these alignments is used to improve the accuracy of inter-species alignments of isoforms. Mirage alignments have also revealed the ubiquity of dual-coding exons, in which an exon conditionally encodes multiple open reading frames as overlapping spliced segments of frame-shifted genomic sequence.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6508070/pdf/nihms-993818.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37231822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of β-strand Twist from the 3-dimensional Image of a Protein. 蛋白质三维图像中β-链扭曲的分析。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2017-08-01

Tunazzina Islam, Michael Poteat, Jing He

引用次数: 0

An Out-of-Core GPU based dimensionality reduction algorithm for Big Mass Spectrometry Data and its application in bottom-up Proteomics. 基于out - core GPU的大质谱数据降维算法及其在自下而上蛋白质组学中的应用。

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine Pub Date : 2017-08-01 DOI: 10.1145/3107411.3107466

Muaaz Gul Awan, Fahad Saeed

{"title":"An Out-of-Core GPU based dimensionality reduction algorithm for Big Mass Spectrometry Data and its application in bottom-up Proteomics.","authors":"Muaaz Gul Awan, Fahad Saeed","doi":"10.1145/3107411.3107466","DOIUrl":"https://doi.org/10.1145/3107411.3107466","url":null,"abstract":"Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and computational operations inside GPU. These novel data structures include Binary Spectra and Quantized Indexed Spectra (QIS). The former helps in communicating essential information between CPU and GPU using minimum amount of data while latter enables us to store and process complex 3-D data structure into a 1-D array structure while maintaining the integrity of MS data. Our proposed algorithm also takes into account the limited memory of GPUs and switches between in-core and out-of-core modes based upon the size of input data. G-MSR achieves a peak speed-up of 386x over its sequential counterpart and is shown to process over a million spectra in just 32 seconds. The code for this algorithm is available as a GPL open-source at GitHub at the following link: https://github.com/pcdslab/G-MSR.","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3107411.3107466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35469416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8