Characteristics of oligonucleotide frequencies across genomes: Conservation versus variation, strand symmetry, and evolutionary implications

One of the objectives of evolutionary genomics is to reveal the genetic information contained in the primordial genome (called the primary genetic information in this paper, with the primordial genome defined here as the most primitive nucleic acid genome for earth’s life) by searching for primitive traits or relics remained in modern genomes. As the shorter a sequence is, the less probable it would be modified during genome evolution. For that reason, some characteristics of very short nucleotide sequences would have considerable chances to persist during billions of years of evolution. Consequently, conservation of certain genomic features of mononucleotides, dinucleotides, and higher-order oligonucleotides across various genomes may exist; some, if not all, of these features would be relics of the primary genetic information. Based on this assumption, we analyzed the pattern of frequencies of mononucleotides, dinucleotides, and higher-order oligonucleotides of the whole-genome sequences from 458 species (including archaea, bacteria, and eukaryotes). Also, we studied the phenomenon of strand symmetry in these genomes. The results show that the conservation of frequencies of some dinucleotides and higher-order oligonucleotides across genomes does exist, and that strand symmetry is a ubiquitous and explicit phenomenon that may contribute to frequency conservation. We propose a new hypothesis for the origin of strand symmetry and frequency conservation as well as for the constitution of early genomes. We conclude that the phenomena of strand symmetry and the pattern of frequency conservation would be original features of the primary genetic information

Proposing a life cycle land use impact calculation methodology

The Life Cycle Assessment (LCA) community is yet to come to a consensus on a methodology to incorporate land use in LCA. Earlier our research group presented a methodology based on the ecosystem exergy concept. The ecosystem exergy concept suggests that ecosystems develop towards more effective degradation of energy fluxes passing through the system. The concept is argued to be derivable from two axioms: the principles of (i) maximum exergy storage and the (ii) maximum exergy dissipation. In this paper we present a methodology to assess impacts of human induced land use occupation, in which we make a difference between functional and structural land use impacts. The methodology follows a dynamic multi-indicator approach looking at mid-point impacts on soil fertility, soil structure, biomass production, vegetation structure, on-site water balance and biodiversity. The impact scores are calculated as a relative difference with a reference system. We propose to calculate the impact by calculating the land quality change between the former and the actual land use relative to the quality of the potential natural vegetation. Impact scores are then aggregated, as endpoint impacts, in (i) structural land use impact (exergy storage capacity) and (ii) functional land use impact (exergy dissipation capacity). For aggregation of the relative mid-point impact scores no characterization factor is used. In order to fit this impact calculation in the LCA framework the end-point impact scores are multiplied by a LCA component, a component that enables us to report the impact per functional unit

Transpiration in plants: A thermodynamic imperative

In this article we determine the importance of transpiration in plants at three different levels of organization: the plant itself, the ecosystem, and the biosphere, all in terms of entropy production due to transpiration. We propose that transpiration is a thermodynamic imperative rather than a physiological burden for the plant. Plants have not replaced their prevalent metabolism C3 with those of less loss of water, C4 or CAM. We argue that the fact that plants retain higher rates of transpiration along evolution could be explained using thermodynamic criteria.
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Development of human limbs.

This work offers a new view on the developmental history of tetrapods. It proposes an original evolution model of human limbs based on metameric formation of osteogenic buds in accordance to primary segmentation and biplanar symmetry. While going through evolution, osteogenic buds initially identical to each other were changing their sizes, realigning, regressing, uniting while keeping the direction of the formation in accordance to the following formula (taking into account sesamoid bones):
2; 1; 2; 3; 2; 3; 5; 5; 8; 8 (in the upper limb together with the upper limb girdle); 3; 2; 3; 2; 1; 2; 8; 8; 5; 5 (in the lower limb together with the pelvic bones)

Ten Simple Rules for Searching and Organizing the Scientific Literature

The exponentially increasing number of published papers (1.4 million per year by one estimate) makes it more and more difficult for us to manage the flood of scientific information. Each of us has acquired some protocol to find and organize journal articles and other references over the course of our careers. Most of those protocols are likely to have been formed by old routines or idleness rather than a structured approach to save time and frustration over the long run. Furthermore, with the Web 2.0 revolution, new ways of handling information are emerging (O’Reilly 2005). For example, traditional standalone tools for reference management like EndNote are being supplemented by centralized resources like RefWorks and social bookmarking sites as described subsequently. This fusion of personal and public information offers the promise of efficiency through better organization, which in turn leads to better science.

How can seasoned scientists do better using these tools and those newer to the field start off in the right way? To start to answer that question, I present ten simple rules to master the search and organization of new literature. This is not meant to be comprehensive. It represents the experiences of a few and I welcome your thoughts, through comments to this article, on what you do to keep your references organized.

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Towards Desiderata for an Ontology of Diseases for the Annotation of Biological Datasets

There is a plethora of disease ontologies available, all potentially useful for the annotation of biological datasets. We define seven desirable features for such ontologies and examine whether or not these features are supported by eleven disease ontologies. The four ontologies most closely aligned with our desiderata are Disease Ontology, SNOMED CT, NCI thesaurus and UMLS

The modulation of alpha-wave amplitude in human EEG by the intention to act with a motor response

The most conspicuous signal in the human EEG is the so-called alpha wave, oscillations in the frequency range of 8 to 12 Hz. Visual stimulation of the retina suppresses the amplitude of alpha waves (Berger effect), and increased attention can reduce them. Here I show that one more parameter significantly affects the amplitudes of alpha waves: the intention to act by a motor response. Together with data from the literature, these results show that alpha waves are not part of the visual processing network but rather part of a long-range neuromodulatory network. The modulation modifies latencies in perception or motor response. The relevant mechanisms are located in early cortical visual areas; their activity may contribute to hemodynamic changes in these areas and thus explain dissociations between _Bold_ signals and spike activities mentioned in the literature

Soil Carbon in Agroforestry Systems: An Unexplored Treasure?

Soil organic matter (SOM), which contains more reactive organic carbon (C) than any other single terrestrial pool, plays a major role in determining C storage in ecosystems and regulating atmospheric concentrations of carbon dioxide (CO2)^1^. Agroforestry, the practice of growing trees and crops in interacting combinations on the same unit of land^2^, primarily by resource-poor smallholder farmers in developing countries, is recognized as a strategy for soil carbon sequestration (SCS) under the Clean Development Mechanism (CDM) of the Kyoto Protocol^3^. The understanding about C storage and dynamics under agroforestry systems (AFS), however, is minimal. Our studies under various AFS in diverse ecological conditions in five countries showed that tree-based agricultural systems, compared to treeless systems, stored more C in deeper soil layers up to 1 m depth under comparable conditions. More C is stored in soil near the tree than away from the tree; higher SOC content is associated with higher species richness and tree density; and C3 plants (trees) contribute to more C in the silt- + clay-sized (<53 µm) fractions that constitute more stable C, than C4 plants, in deeper soil profiles4 - 8. These results provide clear indications of the possibilities for climate change mitigation through SCS in AFS, and opportunities for economic benefit - through carbon trading - to millions of smallholder farmers in developing countries

In silico Gene Characterization and biological annotation of Aspergillus niger CBS 513.88

Genome annotation is the process of estimation of biological features from genomic data. The target of a genome annotation is to identify the key features of the genome sequence particularly, the genes and gene products. The characteristics of a gene, its products, and gene prediction programs of Aspergillus niger are discussed. Although the number of genomes in genomic databases are increasing day by day, genome-wide analyses are affected by the quality of the genome annotations. This study illustrates the importance of integrative approaches for automatic annotations of genomes of Aspergillus niger by computational methods. However, the annotation process is more complicated in Eukaryotes; we used a comparative study for gene prediction using the FgenesH algorithm by various software providers. The final annotation of Aspergillus niger CBS 513.88. has been created as a GB file in Artemis, A sequence viewer and annotation tool was developed in the anger Institute

Integrative analysis of large-scale biological data sets

We present two novel web-applications for microarray and gene/protein set analysis, ArrayMining.net and TopoGSA. These bioinformatics tools use integrative analysis methods, including ensemble and consensus machine learning techniques, as well as modular combinations of different analysis types, to extract new biological insights from experimental transcriptomics and proteomics data. They enable researchers to combine related algorithms and datasets to increase the robustness and accuracy of statistical analyses and exploit synergies of different computational methods, ranging from statistical learning to optimization and topological network analysis