scholarly journals Identifying gene function and module connections by the integration of multi-species expression compendia

2019 ◽  
Author(s):  
Hao Li ◽  
Daria Rukina ◽  
Fabrice P. A. David ◽  
Terytty Yang Li ◽  
Chang-Myung Oh ◽  
...  
Keyword(s):  
Gene Function ◽  
Large Scale ◽  
Lipid Biosynthesis ◽  
New Method ◽  
Biological Processes ◽  
Gene Module ◽  
Histone Demethylation ◽  
Bioinformatics Tools ◽  
Eukaryotic Genes ◽  
Negative Gene

AbstractThe functions of many eukaryotic genes are still poorly understood. We developed and validated a new method, termed GeneBridge, which is based on two linked approaches to impute gene function and bridge genes with biological processes. First, Gene-Module Association Determination (G-MAD) allows the annotation of gene function. Second, Module-Module Association Determination (M-MAD) allows predicting connectivity among modules. We applied the GeneBridge tools to large-scale multi-species expression compendia—1,700 datasets with over 300,000 samples from human, mouse, rat, fly, worm, and yeast—collected in this study. Unlike most existing bioinformatics tools, GeneBridge exploits both positive and negative gene/module-module associations. We constructed association networks, such as those bridging mitochondria and proteasome, mitochondria and histone demethylation, as well as ribosomes and lipid biosynthesis. The GeneBridge tools together with the expression compendia are available at systems-genetics.org, to facilitate the identification of connections linking genes, modules, phenotypes, and diseases.

New Harvesting and Curing Techniques in the Production of Breeder's Seed Peanuts1

1979 ◽  
Vol 6 (2) ◽  
pp. 70-72
Author(s):  
T. A. Coffelt ◽  
F. S. Wright ◽  
J. L. Steele
Keyword(s):  
Large Scale ◽  
Combine Method ◽  
Frost Damage ◽  
New Method ◽  
Experimental Equipment ◽  
Harvesting Method ◽  
Curing Methods ◽  
Labor Requirements ◽  
High Level ◽  
Varietal Purity

Abstract A new method of harvesting and curing breeder's seed peanuts in Virginia was initiated that would 1) reduce the labor requirements, 2) maintain a high level of germination, 3) maintain varietal purity at 100%, and 4) reduce the risk of frost damage. Three possible harvesting and curing methods were studied. The traditional stack-pole method satisfied the latter 3 objectives, but not the first. The windrow-combine method satisfied the first 2 objectives, but not the last 2. The direct harvesting method satisfied all four objectives. The experimental equipment and curing procedures for direct harvesting had been developed but not tested on a large scale for seed harvesting. This method has been used in Virginia to produce breeder's seed of 3 peanut varieties (Florigiant, VA 72R and VA 61R) during five years. Compared to the stackpole method, labor requirements have been reduced, satisfactory levels of germination and varietal purity have been obtained, and the risk of frost damage has been minimized.

scholarly journals TreeMerge: a new method for improving the scalability of species tree estimation methods

2019 ◽  
Vol 35 (14) ◽  
pp. i417-i426 ◽  
Author(s):  
Erin K Molloy ◽  
Tandy Warnow
Keyword(s):  
Large Scale ◽  
Species Tree ◽  
New Method ◽  
Divide And Conquer ◽  
Supplementary Information ◽  
Estimation Methods ◽  
Running Time ◽  
Tree Estimation ◽  
Computationally Intensive ◽  
A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

A New Method Tracing Load-Deflection Equilibrium Path of a Doubly Nonlinear Truss

2012 ◽  
Vol 166-169 ◽  
pp. 68-72
Author(s):  
Shu Tang Liu ◽  
Qi Liang Long
Keyword(s):  
Matrix Equation ◽  
Stiffness Matrix ◽  
Large Scale ◽  
New Method ◽  
Truss Structure ◽  
Equilibrium Path ◽  
Nodal Coordinates ◽  
Doubly Nonlinear ◽  
Global Stiffness Matrix

A new method tracing the load-deflection equilibrium path of a truss with doubly nonlinearity is proposed. The total global stiffness matrix equation has been formulated in terms of nodal coordinates, iteration formulations has been written through adopting a single control coordinate, so that an new method tracing the load-deflection equilibrium path has been proposed. Analysis results of Star dome truss and Schwedeler dome truss have shown that the proposed method is stable numerically, quick in convergence, high in degree of accuracy and easy in use. The proposed method can be used for large-scale truss structure.

Large scale gene regulatory network inference with a multi-level strategy

2016 ◽  
Vol 12 (2) ◽  
pp. 588-597 ◽  
Author(s):  
Jun Wu ◽  
Xiaodong Zhao ◽  
Zongli Lin ◽  
Zhifeng Shao
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Large Scale ◽  
Network Inference ◽  
Biological Processes ◽  
Molecular Processes ◽  
Gene Regulatory Network Inference ◽  
Cell Functions ◽  
Multi Level ◽  
Gene Regulatory

Transcriptional regulation is a basis of many crucial molecular processes and an accurate inference of the gene regulatory network is a helpful and essential task to understand cell functions and gain insights into biological processes of interest in systems biology.

Dehydration-induced proteomic landscape of mitochondria in chickpea reveals large-scale coordination of key biological processes

2019 ◽  
Vol 192 ◽  
pp. 267-279 ◽  
Author(s):  
Dipak Gayen ◽  
Saurabh Gayali ◽  
Pragya Barua ◽  
Nilesh Vikram Lande ◽  
Swati Varshney ◽  
...  
Keyword(s):  
Large Scale ◽  
Biological Processes

ChemInform Abstract: New Method of Purification of HF Chemicals for Very Large Scale Integration (VLSI) Manufacturing.

ChemInform ◽  
2010 ◽  
Vol 28 (14) ◽  
pp. no-no
Author(s):  
K. YAMAMOTO ◽  
T. SHIMONO ◽  
T. OKADA ◽  
Y. KAWAZAWA ◽  
T. TATSUNO
Keyword(s):  
Large Scale ◽  
Very Large Scale Integration ◽  
New Method ◽  
Large Scale Integration ◽  
Scale Integration

scholarly journals Hidden in plain sight: What remains to be discovered in the eukaryotic proteome?

2018 ◽  
Author(s):  
Valerie Wood ◽  
Antonia Lock ◽  
Midori A. Harris ◽  
Kim Rutherford ◽  
Jürg Bähler ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Fission Yeast ◽  
Genome Sequencing ◽  
Large Scale ◽  
Biological Process ◽  
Blind Spot ◽  
Model Organisms ◽  
Biological Processes ◽  
Health And Disease

AbstractThe first decade of genome sequencing stimulated an explosion in the characterization of unknown proteins. More recently, the pace of functional discovery has slowed, leaving around 20% of the proteins even in well-studied model organisms without informative descriptions of their biological roles. Remarkably, many uncharacterized proteins are conserved from yeasts to human, suggesting that they contribute to fundamental biological processes. To fully understand biological systems in health and disease, we need to account for every part of the system. Unstudied proteins thus represent a collective blind spot that limits the progress of both basic and applied biosciences.We use a simple yet powerful metric based on Gene Ontology (GO) biological process terms to define characterized and uncharacterized proteins for human, budding yeast, and fission yeast. We then identify a set of conserved but unstudied proteins in S. pombe, and classify them based on a combination of orthogonal attributes determined by large-scale experimental and comparative methods. Finally, we explore possible reasons why these proteins remain neglected, and propose courses of action to raise their profile and thereby reap the benefits of completing the catalog of proteins’ biological roles.

scholarly journals CrosstalkNet: mining large-scale bipartite co-expression networks to characterize epi-stroma crosstalk

2017 ◽  
Author(s):  
Venkata Manem ◽  
George Adam ◽  
Tina Gruosso ◽  
Mathieu Gigoux ◽  
Nicholas Bertos ◽  
...  
Keyword(s):  
Stromal Cells ◽  
Large Scale ◽  
Network Visualization ◽  
Visualization Tool ◽  
Biological Processes ◽  
Web Based ◽  
Link Type ◽  
A Cell ◽  
Large Scale Networks ◽  
User Friendly

ABSTRACTBackground:Over the last several years, we have witnessed the metamorphosis of network biology from being a mere representation of molecular interactions to models enabling inference of complex biological processes. Networks provide promising tools to elucidate intercellular interactions that contribute to the functioning of key biological pathways in a cell. However, the exploration of these large-scale networks remains a challenge due to their high-dimensionality.Results:CrosstalkNet is a user friendly, web-based network visualization tool to retrieve and mine interactions in large-scale bipartite co-expression networks. In this study, we discuss the use of gene co-expression networks to explore the rewiring of interactions between tumor epithelial and stromal cells. We show how CrosstalkNet can be used to efficiently visualize, mine, and interpret large co-expression networks representing the crosstalk occurring between the tumour and its microenvironment.Conclusion:CrosstalkNet serves as a tool to assist biologists and clinicians in exploring complex, large interaction graphs to obtain insights into the biological processes that govern the tumor epithelial-stromal crosstalk. A comprehensive tutorial along with case studies are provided with the application.Availability:The web-based application is available at the following location: http://epistroma.pmgenomics.ca/app/. The code is open-source and freely available from http://github.com/bhklab/EpiStroma-webapp.Contact:[email protected]

Turbulence, diffusion and patchiness in the sea

1994 ◽  
Vol 343 (1303) ◽  
pp. 11-18 ◽  
Keyword(s):  
Large Scale ◽  
Approximate Model ◽  
Inertial Subrange ◽  
Biological Processes ◽  
Two Dimensional ◽  
Predator Prey ◽  
Interacting Populations ◽  
Terrestrial Environments ◽  
Population Interactions ◽  
Passive Tracers

We explore the role that biological processes play in the patchiness of plankton populations in the sea. We ask how population interactions modify the variance in plankton density as a function of spatial scale (i.e. the variance spectrum) from that expected if the biota were merely passive tracers. Using an approximate model for two limiting cases of turbulence - the inertial subrange and two-dimensional turbulence - we consider a simple predator - prey formulation for interacting populations in a turbulent ocean. No simple generalizations emerge. T he interacting populations ‘redden’ (i.e. more variance at large scale) the spectrum of the passive tracers in the inertial subrange. Conversely, the interaction ‘whitens’ (i.e. less variance at large scale) the passive tracer spectrum for two-dimensional turbulence. This mirrors results in terrestrial environments.

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