Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )最新文献

{"title":"Genomewide Identification and Expression Analyses of PAL Genes in Different Color Radish","authors":"Biao Lai, Chun-Yu Chen, Zehui Tang, Jing Xiao, Qi Wang, Fabo Chen, Lina Du","doi":"10.5376/cmb.2022.12.0001","DOIUrl":"https://doi.org/10.5376/cmb.2022.12.0001","url":null,"abstract":"","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79230435","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}

{"title":"Cloning and Expression Analysis of Phytoene Desaturase (PDS) Gene from Mango (Mangifera indica L)","authors":"Kaili Yu, Zhichang Zhao, A. Gao, R. Luo, Jianfeng Huang, Mengyun Zhang, Maofu Li","doi":"10.5376/cmb.2022.12.0004","DOIUrl":"https://doi.org/10.5376/cmb.2022.12.0004","url":null,"abstract":"Phytoene desaturase (PDS) affects the synthesis of carotenoids. It is a key gene in the carotenoids biosynthesis pathway. In order to study the function of PDS gene from mango fruits, the phytoene dehydrogenase ( PDS ) gene of ‘ Guifei ’ mango fruit was obtained with RACE methods. The full-length cDNA sequence of the gene is 1 820 bp, open reading frame is 1 650 bp, encoding 549 amino acids, the molecular weight is 61.34 KD, and the isoelectric point is 6.78. It was cluster analysis found that the mango PDS protein had a close relationship with grapefruit, cantaloupe, and papaya. Its amino acid composition is mainly alanine (ALa), leucine (Leu), valine (Val), and so on. Expression of PDS gene in different varieties by PCR showed: the high expression of the red ‘ Guifei ’ varieties and the expression of green mango varieties with low volume. Prediction of the domain, tertiary structure, and interaction protein of its protein, found to contain phytoene-desat, PLNO2487 superfamily, and other domains. The use of the STRING database found PDS interacted with proteins such as PSY, ZDS, and CRTISO. This research will be valuable for understanding the molecular mechanism of gene regulation in carotenoid biosynthesis and can be served as the basis for the metabolic engineering of mango.","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"110 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76104665","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}

{"title":"Privacy-Preserving Genotype Imputation in a Trusted Execution Environment.","authors":"Natnatee Dokmai, Can Kockan, Kaiyuan Zhu, XiaoFeng Wang, S Cenk Sahinalp, Hyunghoon Cho","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"12 10","pages":"983-993.e7"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635452/pdf/nihms-1713574.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39940700","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}

{"title":"Molecular Evolution of Genes Involved in Quinic Acid Utilization in Fungi","authors":"D. Asch, Jannet Ziegler, X. Min","doi":"10.5376/cmb.2021.11.0005","DOIUrl":"https://doi.org/10.5376/cmb.2021.11.0005","url":null,"abstract":"Fungi use diverse organic compounds for their growth and development.  Neurospora crassa  can use quinic acid as its sole carbon source for its growth because of presence of a quinic acid utilization (QUT) cluster of genes in its genome. Using bioinformatics methods we examined a total of 285 completely sequenced fungal genomes comprised of 282 unique species and found there were 117 fungal species having all 7 QUT genes in their genomes. Most species in the classes of Dothideomycetes, Eurotiomycetes, Leotiomycetes and Sordariomycetes have QUT genes, however, among 53 species in Saccharomycetes only 3 species have all 7 QUT genes. There were linage specific losses of QUT genes, such as species in Eurotiomycetes class Onygenales order lacked most of QA utilization genes. Our survey revealed that species in Agaricomycetes, Basidiomycota, Chytridiomycetes, Exobasidiomycetes, Malasseziomycetes, Microsporidia, Schizosacharomycetes, and Tremellomycetes did not have QA utilization genes. Using concatenated protein sequences encoded by 7 QUT genes, a robust phylogenetic tree to infer the evolution of the QUT cluster genes was constructed. In addition, we also found QUT genes from recently sequenced genome of cork oak ( Quercus suber ), however, our analysis suggests that these QUT sequences are likely from a contaminated fungal species.","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79709371","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}

{"title":"Advances in Transcriptome Analyses Using RNA Sequencing Technology in Soybean Plants [Glycine max]","authors":"J. Min, Mykaela Wagner, Theoni Kasamias","doi":"10.5376/CMB.2021.11.0001","DOIUrl":"https://doi.org/10.5376/CMB.2021.11.0001","url":null,"abstract":"Soybean [Glycine max] is an important oil and food plant for both humans and animals. Recent development in RNA sequencing (RNA-seq) technology provides a cost effective approach to analyzing transcriptomes of plants at different developmental stages and in responses to different biotic and abiotic challenges. Currently there are over 5 000 RNA-seq datasets in soybean plants publicly available at SRA database in the National Center for Biotechnology Information (NCBI). Such a large number of RNA-seq datasets provide soybean researchers an opportunity as well as a challenge for fully exploring the data to understand soybean biology. A number of research articles have been published on applications of RNA-seq in transcriptome analysis of soybean plants, covering a wide range of topics including growth and development, plant mineral nutrients, responses to environmental stresses, pathogens and pests. In this work we compile and review recent advances of RNA-seq transcriptome analyses including profiling of differential gene expression, gene alternative splicing, and gene regulatory networks in soybean plants, with key findings excerpted from each individual published article.","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89387922","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}

{"title":"A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets.","authors":"Barış Ekim, Bonnie Berger, Yaron Orenstein","doi":"10.1007/978-3-030-45257-5_3","DOIUrl":"10.1007/978-3-030-45257-5_3","url":null,"abstract":"<p><p>As the volume of next generation sequencing data increases, an urgent need for algorithms to efficiently process the data arises. <i>Universal hitting sets</i> (UHS) were recently introduced as an alternative to the central idea of minimizers in sequence analysis with the hopes that they could more efficiently address common tasks such as computing hash functions for read overlap, sparse suffix arrays, and Bloom filters. A UHS is a set of <math><mi>k</mi></math>-mers that hit every sequence of length <math><mi>L</mi></math>, and can thus serve as indices to <math><mi>L</mi></math>-long sequences. Unfortunately, methods for computing small UHSs are not yet practical for real-world sequencing instances due to their serial and deterministic nature, which leads to long runtimes and high memory demands when handling typical values of <math><mi>k</mi></math> (e.g. <math><mrow><mi>k</mi><mo>></mo><mn>13</mn></mrow></math>). To address this bottleneck, we present two algorithmic innovations to significantly decrease runtime while keeping memory usage low: (i) we leverage advanced theoretical and architectural techniques to parallelize and decrease memory usage in calculating <math><mi>k</mi></math>-mer hitting numbers; and (ii) we build upon techniques from randomized Set Cover to select universal <math><mi>k</mi></math>-mers much faster. We implemented these innovations in PASHA, the first randomized parallel algorithm for generating nearoptimal UHSs, which newly handles <math><mrow><mi>k</mi><mo>></mo><mn>13</mn></mrow></math>. We demonstrate empirically that PASHA produces sets only slightly larger than those of serial deterministic algorithms; moreover, the set size is provably guaranteed to be within a small constant factor of the optimal size. PASHA's runtime and memory-usage improvements are orders of magnitude faster than the current best algorithms. We expect our newly-practical construction of UHSs to be adopted in many high-throughput sequence analysis pipelines.</p>","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"12074 ","pages":"37-53"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141249251","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}

{"title":"RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy.","authors":"Sneha Mitra, Jianling Zhong, David M MacAlpine, Alexander J Hartemink","doi":"10.1007/978-3-030-45257-5_9","DOIUrl":"10.1007/978-3-030-45257-5_9","url":null,"abstract":"<p><p>Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of occupancy of different transcription factors (TFs) and nucleosomes is therefore crucial to understanding gene regulation. Antibody-based methods for assaying chromatin occupancy are capable of identifying the binding sites of specific DNA binding factors, but only one factor at a time. On the other hand, epigenomic accessibility data like ATAC-seq, DNase-seq, and MNase-seq provide insight into the chromatin landscape of all factors bound along the genome, but with minimal insight into the identities of those factors. Here, we present RoboCOP, a multivariate state space model that integrates chromatin information from epigenomic accessibility data with nucleotide sequence to compute genome-wide probabilistic scores of nucleosome and TF occupancy, for hundreds of different factors at once. RoboCOP can be applied to any epigenomic dataset that provides quantitative insight into chromatin accessibility in any organism, but here we apply it to MNase-seq data to elucidate the protein-binding landscape of nucleosomes and 150 TFs across the yeast genome. Using available protein-binding datasets from the literature, we show that our model more accurately predicts the binding of these factors genome-wide.</p>","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"12074 ","pages":"136-151"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356533/pdf/nihms-1727027.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39306371","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}

{"title":"Research in Computational Molecular Biology: 24th Annual International Conference, RECOMB 2020, Padua, Italy, May 10–13, 2020, Proceedings","authors":"","doi":"10.1007/978-3-030-45257-5","DOIUrl":"https://doi.org/10.1007/978-3-030-45257-5","url":null,"abstract":"","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78117909","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}

{"title":"Context-Specific Nested Effects Models.","authors":"Yuriy Sverchkov,&nbsp;Yi-Hsuan Ho,&nbsp;Audrey Gasch,&nbsp;Mark Craven","doi":"10.1007/978-3-319-89929-9_13","DOIUrl":"https://doi.org/10.1007/978-3-319-89929-9_13","url":null,"abstract":"<p><p>Advances in systems biology have made clear the importance of network models for capturing knowledge about complex relationships in gene regulation, metabolism, and cellular signaling. A common approach to uncovering biological networks involves performing perturbations on elements of the network, such as gene knockdown experiments, and measuring how the perturbation affects some reporter of the process under study. In this paper, we develop context-specific nested effects models (CSNEMs), an approach to inferring such networks that generalizes nested effect models (NEMs). The main contribution of this work is that CSNEMs explicitly model the participation of a gene in multiple <i>contexts</i>, meaning that a gene can appear in multiple places in the network. Biologically, the representation of regulators in multiple contexts may indicate that these regulators have distinct roles in different cellular compartments or cell cycle phases. We present an evaluation of the method on simulated data as well as on data from a study of the sodium chloride stress response in <i>Saccharomyces cerevisiae</i>.</p>","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"10812 ","pages":"194-210"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342457/pdf/nihms-1001013.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36895231","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}

{"title":"Generalizable visualization of mega-scale single-cell data.","authors":"Hyunghoon Cho,&nbsp;Bonnie Berger,&nbsp;Jian Peng","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":74675,"journal":{"name":"Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )","volume":"10812 ","pages":"251-253"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5917073/pdf/nihms959802.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36068026","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}