Bioinformatics, Comparative Genomics and Molecular Evolution
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Context effects produced by question orders reveal quantum nature of human judgments

Arjen ten Have's insight:
So do you still believe in free will? I must say, this flabbergasts me but this is just sooooooooooo nice. Good start of the week! In recent years, quantum probability theory has been used to explain a range of seemingly irrational human decision-making behaviors. The quantum models generally outperform traditional models in fitting human data, but both modeling approaches require optimizing parameter values. However, quantum theory makes a universal, nonparametric prediction for differing outcomes when two successive questions (e.g., attitude judgments) are asked in different orders. Quite remarkably, this prediction was strongly upheld in 70 national surveys carried out over the last decade (and in two laboratory experiments) and is not one derivable by any known cognitive constraints. The findings lend strong support to the idea that human decision making may be based on quantum probability
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Mel Melendrez-Vallard's curator insight, June 17, 2014 8:17 AM

Great Insight from Arjen ten Have's:

"So do you still believe in free will? I must say, this flabbergasts me but this is just sooooooooooo nice. Good start of the week! In recent years, quantum probability theory has been used to explain a range of seemingly irrational human decision-making behaviors. The quantum models generally outperform traditional models in fitting human data, but both modeling approaches require optimizing parameter values. However, quantum theory makes a universal, nonparametric prediction for differing outcomes when two successive questions (e.g., attitude judgments) are asked in different orders. Quite remarkably, this prediction was strongly upheld in 70 national surveys carried out over the last decade (and in two laboratory experiments) and is not one derivable by any known cognitive constraints. The findings lend strong support to the idea that human decision making may be based on quantum probability"
Bioinformatics, Comparative Genomics and Molecular Evolution
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Rescooped by Arjen ten Have from Plant Pathogenomics
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Genome Biology and Evolution: A Tale of Genome Compartmentalization: The Evolution of Virulence Clusters in Smut Fungi (2016)

Genome Biology and Evolution: A Tale of Genome Compartmentalization: The Evolution of Virulence Clusters in Smut Fungi (2016) | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

Smut fungi are plant pathogens mostly parasitizing wild species of grasses as well as domesticated cereal crops. Genome analysis of several smut fungi including Ustilago maydis revealed a singular clustered organization of genes encoding secreted effectors. In U. maydis, many of these clusters have a role in virulence. Reconstructing the evolutionary history of clusters of effector genes is difficult because of their intrinsically fast evolution, which erodes the phylogenetic signal and homology relationships. Here, we describe the use of comparative evolutionary analyses of quality draft assemblies of genomes to study the mechanisms of this evolution. We report the genome sequence of a South African isolate of Sporisorium scitamineum, a smut fungus parasitizing sugar cane with a phylogenetic position intermediate to the two previously sequenced species U. maydisand Sporisorium reilianum. We show that the genome of S. scitamineumcontains more and larger gene clusters encoding secreted effectors than any previously described species in this group. We trace back the origin of the clusters and find that their evolution is mainly driven by tandem gene duplication. In addition, transposable elements play a major role in the evolution of the clustered genes. Transposable elements are significantly associated with clusters of genes encoding fast evolving secreted effectors. This suggests that such clusters represent a case of genome compartmentalization that restrains the activity of transposable elements on genes under diversifying selection for which this activity is potentially beneficial, while protecting the rest of the genome from its deleterious effect.


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The Strange Inevitability of Evolution

The Strange Inevitability of Evolution | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Ah, but isn’t all this wonder simply the product of the blind fumbling of Darwinian evolution, that mindless machine which takes random variation and sieves it by natural selection? Well, not quite. You don’t have to be a benighted creationist, nor even a believer in divine providence, to argue that Darwin’s astonishing theory doesn’t fully explain why nature is so marvelously, endlessly inventive. “Darwin’s theory surely is the most important intellectual achievement of his time, perhaps of all time,” says evolutionary biologist Andreas Wagner of the University of Zurich. “But the biggest mystery about evolution eluded his theory. And he couldn’t even get close to solving it.”

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Mustread for every biologist
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Can we open the black box of AI?

Can we open the black box of AI? | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Artificial intelligence is everywhere. But before scientists trust it, they first need to understand how machines learn.

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The Diversification of Plant NBS-LRR Defense Genes Directs the Evolution of MicroRNAs That Target Them

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KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins

KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea : Nature : Nature Research

The genome of the seagrass Zostera marina reveals angiosperm adaptation to the sea : Nature : Nature Research | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Seagrasses colonized the sea on at least three independent occasions to form the basis of one of the most productive and widespread coastal ecosystems on the planet. Here we report the genome of Zostera marina (L.), the first, to our knowledge, marine angiosperm to be fully sequenced. This reveals unique insights into the genomic losses and gains involved in achieving the structural and physiological adaptations required for its marine lifestyle, arguably the most severe habitat shift ever accomplished by flowering plants. Key angiosperm innovations that were lost include the entire repertoire of stomatal genes, genes involved in the synthesis of terpenoids and ethylene signalling, and genes for ultraviolet protection and phytochromes for far-red sensing. Seagrasses have also regained functions enabling them to adjust to full salinity. Their cell walls contain all of the polysaccharides typical of land plants, but also contain polyanionic, low-methylated pectins and sulfated galactans, a feature shared with the cell walls of all macroalgae and that is important for ion homoeostasis, nutrient uptake and O2/CO2 exchange through leaf epidermal cells. The Z. marina genome resource will markedly advance a wide range of functional ecological studies from adaptation of marine ecosystems under climate warming, to unravelling the mechanisms of osmoregulation under high salinities that may further inform our understanding of the evolution of salt tolerance in crop plants.
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What a nice system to study evolution!
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Combining dependent P-values with an empirical adaptation of Brown’s method

Combining dependent P-values with an empirical adaptation of Brown’s method | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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Great resource for those not strong in statistics.
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Computing Biology

Computing Biology | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Is Computational Biology increasingly—and steadily—progressing toward addressing the mammoth challenge of actually computing biology? That is, have we reached the stage where we do not support biological research but drive it? This question is vitally important for all—young and established computational biologists. Even though forecasting future research can be risky, we still venture to predict that the future will see considerably more research projects drifting toward this ambitious aspiration. Computational Biology is powerful for abstracting signatures of disease, for predicting it, and for proposing medications. It is effective in figuring out disease mechanisms and forceful in bridging experimental disciplines to obtain testable predictions. However, perhaps its biggest challenges lie in putting together the available broad and disparate information, devising tools to efficiently and effectively carry out these tasks while sifting through noise and recognizing cell specificity, and most importantly coming up with sound, coherent, and testable schemes.

 

Nussinov R, Papin JA (2016) Computing Biology. PLoS Comput Biol 12(7): e1005050. doi:10.1371/journal.pcbi.1005050


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Arjen ten Have's insight:
Interesting read on the driving source of biological research: Computing Biology?
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Uncalculating cooperation is used to signal trustworthiness

Uncalculating cooperation is used to signal trustworthiness | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
uncal
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Things in game theory are starting to fall together.
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Structure-based discovery of opioid analgesics with reduced side effects : Nature : Nature Research

Structure-based discovery of opioid analgesics with reduced side effects : Nature : Nature Research | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Structure-based discovery of opioid analgesics with reduced side effects
Arjen ten Have's insight:
What Bioinformatics can do for you! There goes the pain!
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Rescooped by Arjen ten Have from Plants and Microbes
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PLOS ONE: Directed Evolution of FLS2 towards Novel Flagellin Peptide Recognition (2016)

PLOS ONE: Directed Evolution of FLS2 towards Novel Flagellin Peptide Recognition (2016) | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

Microbe-associated molecular patterns (MAMPs) are molecules, or domains within molecules, that are conserved across microbial taxa and can be recognized by a plant or animal immune system. Although MAMP receptors have evolved to recognize conserved epitopes, the MAMPs in some microbial species or strains have diverged sufficiently to render them unrecognizable by some host immune systems. In this study, we carried out in vitro evolution of the Arabidopsis thaliana flagellin receptor FLAGELLIN-SENSING 2 (FLS2) to isolate derivatives that recognize one or more flagellin peptides from bacteria for which the wild-type Arabidopsis FLS2 confers little or no response. A targeted approach generated amino acid variation at FLS2 residues in a region previously implicated in flagellin recognition. The primary screen tested for elevated response to the canonical flagellin peptide from Pseudomonas aeruginosa, flg22. From this pool, we then identified five alleles of FLS2 that confer modest (quantitatively partial) recognition of an Erwinia amylovora flagellin peptide. Use of this Erwinia-based flagellin peptide to stimulate Arabidopsis plants expressing the resulting FLS2 alleles did not lead to a detectable reduction of virulent P. syringae pv. tomato growth. However, combination of two identified mutations into a single allele further increased FLS2-mediated responses to the E. amylovora flagellin peptide. These studies demonstrate the potential to raise the sensitivity of MAMP receptors toward particular targets.


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Metagenomics: Pathogen diagnostics for the masses : Nature Reviews Genetics : Nature Publishing Group

Metagenomics: Pathogen diagnostics for the masses : Nature Reviews Genetics : Nature Publishing Group | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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Universality of human microbial dynamics : Nature : Nature Publishing Group

Universality of human microbial dynamics : Nature : Nature Publishing Group | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences, rendering them ineffective or even detrimental. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species. Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies—the Human Microbiome Project and the Student Microbiome Project—we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies.
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The Evolutionary Origins of Hierarchy

The Evolutionary Origins of Hierarchy | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Author Summary Hierarchy is a ubiquitous organizing principle in biology, and a key reason evolution produces complex, evolvable organisms, yet its origins are poorly understood. Here we demonstrate for the first time that hierarchy evolves as a result of the costs of network connections. We confirm a previous finding that connection costs drive the evolution of modularity, and show that they also cause the evolution of hierarchy. We further confirm that hierarchy promotes evolvability in addition to evolvability caused by modularity. Because many biological and human-made phenomena can be represented as networks, and because hierarchy is a critical network property, this finding is immediately relevant to a wide array of fields, from biology, sociology, and medical research to harnessing evolution for engineering.
Arjen ten Have's insight:
Hierarchy evolves as a result of connection cost. How cool!
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An efficient system to fund science: from proposal review to peer-to-peer distributions

An efficient system to fund science: from proposal review to peer-to-peer distributions | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

This paper presents a novel model of science funding that exploits the wisdom of the scientific crowd. Each researcher receives an equal, unconditional part of all available science funding on a yearly basis, but is required to individually donate to other scientists a given fraction of all they receive. Science funding thus moves from one scientist to the next in such a way that scientists who receive many donations must also redistribute the most. As the funding circulates through the scientific community it is mathematically expected to converge on a funding distribution favored by the entire scientific community. This is achieved without any proposal submissions or reviews. The model furthermore funds scientists instead of projects, reducing much of the overhead and bias of the present grant peer review system. Model validation using large-scale citation data and funding records over the past 20 years show that the proposed model could yield funding distributions that are similar to those of the NSF and NIH, and the model could potentially be more fair and more equitable. We discuss possible extensions of this approach as well as science policy implications.

 

An efficient system to fund science: from proposal review to peer-to-peer distributions

Johan Bollen, David Crandall, Damion Junk, Ying Ding, Katy Börner

Scientometrics (2016). doi:10.1007/s11192-016-2110-3


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Control principles of complex systems

Control principles of complex systems | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

A reflection of our ultimate understanding of a complex system is our ability to control its behavior. Typically, control has multiple prerequisites: it requires an accurate map of the network that governs the interactions between the system’s components, a quantitative description of the dynamical laws that govern the temporal behavior of each component, and an ability to influence the state and temporal behavior of a selected subset of the components. With deep roots in dynamical systems and control theory, notions of control and controllability have taken a new life recently in the study of complex networks, inspiring several fundamental questions: What are the control principles of complex systems? How do networks organize themselves to balance control with functionality? To address these questions here recent advances on the controllability and the control of complex networks are reviewed, exploring the intricate interplay between the network topology and dynamical laws. The pertinent mathematical results are matched with empirical findings and applications. Uncovering the control principles of complex systems can help us explore and ultimately understand the fundamental laws that govern their behavior.

 

Control principles of complex systems
Yang-Yu Liu and Albert-László Barabási
Rev. Mod. Phys. 88, 035006


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Optimal design of gene knockout experiments for gene regulatory network inference

Optimal design of gene knockout experiments for gene regulatory network inference | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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Seems to me this is applicable to metabolic studies as well!
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Ewan's Blog: Bioinformatician at large: Sharing clinical data: everyone wins

Ewan's Blog: Bioinformatician at large: Sharing clinical data: everyone wins | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
Arjen ten Have's insight:
Most of it is kind of obvious and certainly this is in no way exclusive to clinical data but still this is a nice, simple essay.
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Rescooped by Arjen ten Have from Plant Pathogenomics
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Genome Research: Transposons passively and actively contribute to evolution of the two-speed genome of a fungal pathogen (2016)

Genome Research: Transposons passively and actively contribute to evolution of the two-speed genome of a fungal pathogen (2016) | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

Genomic plasticity enables adaptation to changing environments, which is especially relevant for pathogens that engage in 'arms races' with their hosts. In many pathogens, genes mediating virulence cluster in highly variable, transposon-rich, physically distinct genomic compartments. However, understanding of the evolution of these compartments, and the role of transposons therein, remains limited. Here, we show that transposons are the major driving force for adaptive genome evolution in the fungal plant pathogen Verticillium dahliae. We show that highly variable lineage-specific (LS) regions evolved by genomic rearrangements that are mediated by erroneous double-strand repair, often utilizing transposons. We furthermore show that recent genetic duplications are enhanced in LS regions, against an older episode of duplication events. Finally, LS regions are enriched in active transposons, which contribute to local genome plasticity. Thus, we provide evidence for genome shaping by transposons, both in an active and passive manner, which impacts the evolution of pathogen virulence.


Via Kamoun Lab @ TSL
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Computational biology, Evolution and plant pathology in one!
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Science: Basidiomycete yeasts in the cortex of ascomycete macro lichens (2016)

Science: Basidiomycete yeasts in the cortex of ascomycete macro lichens (2016) | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it

For over 140 years, lichens have been regarded as a symbiosis between a single fungus, usually an ascomycete, and a photosynthesizing partner. Other fungi have long been known to occur as occasional parasites or endophytes, but the one lichen–one fungus paradigm has seldom been questioned. Here we show that many common lichens are composed of the known ascomycete, the photosynthesizing partner, and, unexpectedly, specific basidiomycete yeasts. These yeasts are embedded in the cortex, and their abundance correlates with previously unexplained variations in phenotype. Basidiomycete lineages maintain close associations with specific lichen species over large geographical distances and have been found on six continents. The structurally important lichen cortex, long treated as a zone of differentiated ascomycete cells, appears to consistently contain two unrelated fungi.


Via Kamoun Lab @ TSL
Arjen ten Have's insight:
Postgenome research will definitely change the face of biological research. Yet another example here. Why should an interaction hold two partners?
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Ecological consequences of human niche construction: Examining long-term anthropogenic shaping of global species distributions

Ecological consequences of human niche construction: Examining long-term anthropogenic shaping of global species distributions | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
National Academy of Sciences
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PLOS Collections: Article collections published by the Public Library of Science

PLOS Collections: Article collections published by the Public Library of Science | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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As if I do not have enough stuff to read!
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Proteomics/Introduction to Proteomics - Wikibooks, open books for an open world

Proteomics/Introduction to Proteomics - Wikibooks, open books for an open world | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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Excellent resource for bioinformaticians!!
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Evolution: Duplicate gene co-regulation slows evolution : Nature Reviews Genetics : Nature Publishing Group

Evolution: Duplicate gene co-regulation slows evolution : Nature Reviews Genetics : Nature Publishing Group | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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Determinants of genetic diversity : Nature Reviews Genetics : Nature Publishing Group

Determinants of genetic diversity : Nature Reviews Genetics : Nature Publishing Group | Bioinformatics, Comparative Genomics and Molecular Evolution | Scoop.it
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