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Granular clustering ofde novoprotein models

Dmytro Guzenko, Sergei V. Strelkov
2016 Bioinformatics  
Modern algorithms for de novo prediction of protein structures typically output multiple full-length models (decoys) rather than a single solution.  ...  Here we propose a novel clustering algorithm that natively operates in the space of partial models through an approach known as granular clustering (GC).  ...  Introduction Protein de novo 3-dimensional (3D) structure prediction involves extensive sampling of the conformation space in search of the near-native low energy state.  ... 
doi:10.1093/bioinformatics/btw628 pmid:28171609 fatcat:chbbltjsvrevll6gkhjpftkb6m

Methodologies for the De Novo Discovery of Transposable Element Families

Jessica M. Storer, Robert Hubley, Jeb Rosen, Arian F. A. Smit
2022 Genes  
De Novo methods have been developed; however, a fully automated and accurate approach to the development of complete libraries remains elusive.  ...  In this review, we cover established methods and recent developments in De Novo TE analysis.  ...  Table 1 . 1 De novo methods. Granularity Library Generation Table 2 . 2 Signature-based methods. Granularity Library Generation Table 2 . 2 Cont.  ... 
doi:10.3390/genes13040709 pmid:35456515 pmcid:PMC9025800 fatcat:myjoqcizkfgvzc5juz662j4m5a

Capacity of the Golgi Apparatus for Cargo Transport Prior to Complete Assembly

Shu Jiang, Sung W. Rhee, Paul A. Gleeson, Brian Storrie, Vivek Malhotra
2006 Molecular Biology of the Cell  
In the case of de novo Golgi formation from the ER after brefeldin A/H89 washout in HeLa cells, we found that scattered, golgin-enriched, structures formed early and contained golgins including giantin  ...  In yeast, particular emphasis has been given to endoplasmic reticulum (ER)-derived, cisternal maturation models of Golgi assembly while in mammalian cells more emphasis has been given to golgins as a potentially  ...  ACKNOWLEDGMENTS We gratefully acknowledge the expert technical assistance of Terry Fletcher and Demond Williams. We express our appreciation for gifts of antibodies as cited in Materials and Methods.  ... 
doi:10.1091/mbc.e05-12-1112 pmid:16837554 pmcid:PMC1556386 fatcat:h5q374e26jhtrozrh2oxosoose

Complex signatures of genomic variation of two non-model marine species in a homogeneous environment

Erica S. Nielsen, Romina Henriques, Robert J. Toonen, Ingrid S. S. Knapp, Baocheng Guo, Sophie von der Heyden
2018 BMC Genomics  
Genomic tools are increasingly being used on non-model organisms to provide insights into population structure and variability, including signals of selection.  ...  Conclusions: Our study provides a background for comparative genomic studies focused on non-model species, as well as a baseline for the adaptive potential of marine invertebrates along the South African  ...  Acknowledgements SvdH thanks Stellenbosch University for a Discretionary Grant, as well as the National Research Foundation of South Africa for Grant 92788 awarded through the Competitive Support for Rated  ... 
doi:10.1186/s12864-018-4721-y pmid:29743012 pmcid:PMC5944137 fatcat:y6cx2sgtavd2tf6shdh4kohhje

Nucleolar Proteins and Nuclear Ultrastructure in Preimplantation Bovine Embryos Produced In Vitro1

J. Laurincik, P.D. Thomsen, A. Hay-Schmidt, B. Avery, T. Greve, R.L. Ochs, P. Hyttel
2000 Biology of Reproduction  
The aim of the present investigation was to describe the basic cell biology of the postfertilization activation of rRNA genes using in vitro-produced bovine embryos as a model.  ...  Subsequently, the presumptive granular component (GC) gradually became embedded in the substance of this entity, resulting in the formation of a fibrillo-granular nucleolus.  ...  Furthermore, if the proteins are synthesized de novo, they may result from transcripts inherited from the oocyte or from de novo transcription of the embryonic genome.  ... 
doi:10.1095/biolreprod62.4.1024 pmid:10727273 fatcat:c65xyva6knb35jb5cleqwgfcpm

Coordinating the impact of structural genomics on the human α-helical transmembrane proteome

Ursula Pieper, Avner Schlessinger, Edda Kloppmann, Geoffrey A Chang, James J Chou, Mark E Dumont, Brian G Fox, Petra Fromme, Wayne A Hendrickson, Michael G Malkowski, Douglas C Rees, David L Stokes (+6 others)
2013 Nature Structural & Molecular Biology  
Structures of 100 optimally selected targets would increase the fraction of modelable human α-helical transmembrane domains from 26% to 58%, thus providing structure/function information not otherwise  ...  With the recent successes in determining membrane protein structures, we explore the tractability of determining representatives for the entire human membrane proteome.  ...  Progress has recently been made in de novo structure prediction of α-helical membrane protein sequences by relying on a large number of homologous sequences determined by genomic sequencing 11 .  ... 
doi:10.1038/nsmb.2508 pmid:23381628 pmcid:PMC3645303 fatcat:d73f3delyvefbhm242fpzvrdga

From yeast to hypha: defining transcriptomic signatures of the morphological switch in the dimorphic fungal pathogen Ophiostoma novo-ulmi

M. Nigg, L. Bernier
2016 BMC Genomics  
Using RNAseq, we found that over 22% of the genome of O. novo-ulmi is differentially expressed during the transition.  ...  By performing clustering analyses of time series gene expression data, we identified several sets of genes that are differentially expressed according to distinct and representative temporal profiles.  ...  Acknowledgments We thank Brian Boyle and staff from the Plateforme d'Analyses Génomiques Availability of data and materials The data set supporting the results of this article is included within the  ... 
doi:10.1186/s12864-016-3251-8 pmid:27846799 pmcid:PMC5111228 fatcat:gvc6kwlnknhnhh6oxe33u36y24

Unique Features of the Loblolly Pine (Pinus taeda L.) Megagenome Revealed Through Sequence Annotation

J. L. Wegrzyn, J. D. Liechty, K. A. Stevens, L.-S. Wu, C. A. Loopstra, H. A. Vasquez-Gross, W. M. Dougherty, B. Y. Lin, J. J. Zieve, P. J. Martinez-Garcia, C. Holt, M. Yandell (+10 others)
2014 Genetics  
Clustering these gene models with 13 other plant species resulted in 20,646 gene families, of which 1554 are predicted to be unique to conifers.  ...  The gene models for loblolly pine have the highest median and mean intron lengths of 24 fully sequenced plant genomes.  ...  A large inflation value defines more clusters with lower amount of members (fine-grained granularity); a small inflation value defines not as many clusters, but the clusters have more members (coarse granularity  ... 
doi:10.1534/genetics.113.159996 pmid:24653211 pmcid:PMC3948814 fatcat:pyc3ph7gzvgyvmsikanpufwwsm

The Cell Adhesion Molecule Neurofascin Stabilizes Axo-axonic GABAergic Terminals at the Axon Initial Segment

Martin Kriebel, Jennifer Metzger, Sabine Trinks, Deepti Chugh, Robert J. Harvey, Kirsten Harvey, Hansjürgen Volkmer
2011 Journal of Biological Chemistry  
Lentiviral shRNA-mediated knockdown of neurofascin in adult rat brain indicates that neurofascin regulates the number and size of postsynaptic gephyrin scaffolds, the number of GABA A receptor clusters  ...  The cell adhesion molecule neurofascin is localized at the axon initial segment of granular cells in rat dentate gyrus, which is mainly targeted by chandelier cells.  ...  In a previous report, low density cultures of hippocampal neurons served as a model for the de novo formation of gephyrin clusters at the soma and the axon hillock (18) .  ... 
doi:10.1074/jbc.m110.212191 pmid:21576239 pmcid:PMC3129217 fatcat:juq6yg44szalflifpolivaopde

Modeling de novo granulation of anaerobic sludge

Anna Doloman, Honey Varghese, Charles D. Miller, Nicholas S. Flann
2017 BMC Systems Biology  
The model of anaerobic de novo granulation can be used to predict the morphology of the anaerobic granules in a alternative substrates of interest and to estimate methane potential of the resulting microbial  ...  The agent-based model developed in a cDynoMiCs simulation environment successfully demonstrated a de novo granulation in a glucose fed system, with the average specific methanogenic activity of 1.11 ml  ...  Acknowledgments Thanks to Jan-Ulrich Kreft School of Biosciences, University of Birmingham for providing the original version of iDynoMiCs.  ... 
doi:10.1186/s12918-017-0443-z pmid:28716030 pmcid:PMC5514506 fatcat:ylvowc5vfjgxfd23cpedcvlpby

Sparse nonnegative matrix factorization for protein sequence motif discovery

Wooyoung Kim, Bernard Chen, Jingu Kim, Yi Pan, Haesun Park
2011 Expert systems with applications  
The task involves clustering relatively similar protein segments from a huge collection of protein sequences and culling high quality motifs from a set of clusters.  ...  A granular computing strategy combined with K-means clustering algorithm was previously proposed for the task, but this strategy requires a manual selection of biologically meaningful clusters which are  ...  Finally, the authors thank Daniel Lee at Georgia Institute of Technology for his careful reading and commenting of the paper.  ... 
doi:10.1016/j.eswa.2011.04.133 fatcat:vpktygepcvco7auqgcbqn6ramu

Cellular adhesiveness and cellulolytic capacity in Anaerolineae revealed by omics-based genome interpretation

Yu Xia, Yubo Wang, Yi Wang, Francis Y. L. Chin, Tong Zhang
2016 Biotechnology for Biofuels  
Expression of the tight adherence protein on the Tfp indicated its function for cellular attachment which was further testified to be more likely related to cell aggregation other than cellulose surface  ...  The Anaerolineae lineage of Chloroflexi had been identified as one of the core microbial populations in anaerobic digesters; however, the ecological role of the Anaerolineae remains uncertain due to the  ...  Consent for publication All the authors consented on the publication of this work.  ... 
doi:10.1186/s13068-016-0524-z pmid:27222666 pmcid:PMC4877987 fatcat:x6xxl7rr65ck5frzfygawbto24

Keratin 4 Upregulation by Retinoic Acid In Vivo: A Sensitive Marker for Retinoid Bioactivity in Human Epidermis1

Marie Virtanen, Hans Törmä, Anders Vahlquist
2000 Journal of Investigative Dermatology  
In parallel biopsies, immunohistochemistry showed no change in K1, K2e, or K10 staining, but a strong de novo appearance of K4 in the granular layer after retinoid treatment.  ...  Finally, a dose±response study showed that the de novo appearance of K4 can be utilized as a sensitive test for retinoid bioactivity in epidermis in vivo.  ...  We are grateful to Professor I Leigh, London, for the gift of K1, K10, and K2e antibodies, and to Dr. P.E. Bowden, Cardiff, for constructive advice concerning the design of keratin primers.  ... 
doi:10.1046/j.1523-1747.2000.00901.x pmid:10692107 fatcat:t3hxujcv4nfizh3z3mntdnkwai

A De-Novo Genome Analysis Pipeline (DeNoGAP) for large-scale comparative prokaryotic genomics studies

Shalabh Thakur, David S. Guttman
2016 BMC Bioinformatics  
The pipeline is designed to perform reference-assisted and de novo gene prediction, homolog protein family assignment, ortholog prediction, functional annotation, and pan-genome analysis using a range  ...  Results: We have developed a de-novo genome analysis pipeline (DeNoGAP) for the automated, iterative and high-throughput analysis of data from comparative genomics projects involving hundreds of whole  ...  Acknowledgements We acknowledge the value input of the Guttman and Desveaux labs in evaluating this work.  ... 
doi:10.1186/s12859-016-1142-2 pmid:27363390 pmcid:PMC4929753 fatcat:q2dsnzmr4vf6lcft2wv2agqlle

Image3C, a multimodal image-based and label independent integrative method for single-cell analysis

Alice Accorsi, Andrew C Box, Robert Peuß, Christopher Wood, Alejandro Sánchez Alvarado, Nicolas Rohner
2021 eLife  
Image3C exploits intrinsic cellular features and non-species-specific dyes to perform de novo cell composition analysis and to detect changes in cellular composition between different conditions.  ...  ., antibodies) that allow cell identification, clustering and convolutional neural network (CNN) training.  ...  The first 80% of the images were used together with their 712 cluster IDs obtained by the de novo clustering to train the classifier.  ... 
doi:10.7554/elife.65372 pmid:34286692 pmcid:PMC8370771 fatcat:tgch4k3ganbifc3ztq677xcxx4
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