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206 results for “secondary structure”

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zenodo40/100

Fig. 7 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 7 – Comparison of the sizes of foraging areas of polycalic colonies and supercolonies of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges: a, Crimea, b, – Rostov-on-Don, c, Tashkent.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Fig. 6 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 6 – Average values of the average size of the foraging areas of Crematogaster subdentata (a) and Lasius neglectus (b) in the primary and secondary ranges. C – Crimea, T – Tashkent, R – Rostov-on-Don.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Fig. 5 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 5 – Relation of tree and shrub species visited by Crematogaster subdentata (a, Crimea, b, Rostov-on-Don, c, Tashkent) and Lasius neglectus (d, – Crimea, e, – Rostov-on-Don, f, – Tashkent). Trees: Ac – Acer sp., Ah – Aesculus hippocastanum, Aj – Albizia julibrissin, Al – Ailanthus altissima, An – Acer negundo, Cl – Cedrus libani, Co – Cydonia oblonga, Cs – Cupressus sempervirens, Ea – Elaeagnus angustifolia, Fe – Fraxinus excelsior, Fr – Fraxinus sp., Gl – Gleditsia triacanta, Jr – Juglans regia, M – Morus sp., Md – Malus domestica, Mn – Morus nigra, Pa – Prunus americana, Pb - Pinus brutia, Pc – Prunus cerasus, Pd – Prunus domestica, Pi – Pinus pallasiana, Pp – Populus niger, Po – Populus alba, Pr – Prunus cerasifera, Ps – Prunus spinosa, Py - Populus pyramidalis, Ra – Robinia pseudoacacia, Sa – Salix sp., Sj – Styphnolobium japonicum, Tl – Tilia sp., Ul – Ulmus sp., Us – Ulmus laevis.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Fig. 1 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 1 – Distribution of Crematogaster subdentata and Lasius neglectus in Tashkent C. subdentata, polycalic colonies, C. subdentata, monocalic colonies, L. neglectus,> 20 nests per 100 m, L. neglectus, 10-20 nests per 100 m, L. neglectus, <10 nests per 100 m.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Fig. 2 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 2 – Scheme of the foraging areas of Lasius neglectus in Rostov-on-Don species; trees: Pc – Prunus cerasus, Ps – Prunus spinosa, Ul – Ulmus sp.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Fig. 4 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 4 – Scheme of the foraging areas of Crematogaster subdentata in Crimea (A) and Tashkent (B) large accessible nests of C. subdentata in buildings and outside; inaccessible nests of C. subdentata in buildings; trees: Co – Cydonia oblonga, Jr – Juglans regia, M – Morus sp., Md – Malus domestica, Mn – Morus nigra, Pa – Prunus americana, Pd – Prunus domestica.

opencc-by-4.0Mar 2021View details →
zenodo36/100

Predicted secondary structures (2-D representation of this self-folding) of the terminal untranslated regions (UTR) of FvMV1 and FaMV1-162

<p>Schemes (a) and (c) represent the 5`-UTR and 3`-UTR of FvMV1 with dG = -82.52 and dG = -29.55, respectively. Schemes (b) and (d) represent the 5`-UTR and 3`-UTR of FaMV1-162 with dG = -73.96 and dG = -13.93, respectively. The +ssRNA molecules were folded, and the free energy was calculated with the RNA Folding Form V 2.3 Energies (MFOLD) program. For these calculations, the following conditions were sectioned: 25&ordm;C, 1M NaCl and 0M divalent ions. The rendering of the structures has been defined with natural angles and annotated using colored base characters, based on p-num information. Colors are ranged from red to black representing the probability as well-determined (1) to poorly determined (0), respectively.</p>

opencc-by-4.0Aug 2020View details →
zenodo36/100

Supplementary Data for Secondary structure and DNA binding domain prediction

<p><strong>This project contains&nbsp;the following extended data:</strong></p> <ul> <li><strong>Supplementary Table 1: </strong>Summary table of DNA binding domains (DBD), the counts of target regions within the genome and statistical analysis. (DNA_BINDING_DOMAINS_ID.tsv)</li> <li><strong>Sequence</strong>:&nbsp;ecCEBP&alpha; secondary structure prediction with RNAplfold at a pairing probability cut off of 0.1. N represents all sequences with pairing probability greater than 0.1.&nbsp; (predicted_secondary_structure_of_ecCEBPA.fa)</li> </ul>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Improving phonetic alignment by handling secondary sequence structures

<p>Supplementary material accompanying the paper &quot;Improving phonetic alignment by handling secondary sequence structures&quot;.</p> <p>The data consists of 5 files:</p> <ul> <li>gold_standard.psa : the gold standard used in the analysis in PSA format</li> <li>&nbsp;sca-secondary.psa : the output of the algorithm with the secondary extension</li> <li>sca-traditional.psa : the output of the traditional algorithm</li> <li>sca-secondary-diff.psa : the differences of the secondary extension compared to the GS</li> <li>sca-traditional-diff.psa : the differences of the traditional algorithm compared to the GS</li> </ul> <p>For a description of the file-format used in this dataset, please refer to the LingPy tutorial under http://lingpy.org.</p>

opengpl-2.0Jun 2012View details →
dryad36/100

The role of a synanthropic bird in the nest niche expansion of a secondary cavity-nester to man-made structures

<p><span>Species with similar ecological characters often compete with each other; however, a species may also facilitate the survival or reproduction of another ecologically similar species although such interaction is rarely documented in birds. Here we reported a facilitative species interaction between Asian house martins (<em>Delichon dasypus</em>) and russet sparrows (<em>Passer cinnamomeus</em>), both passerines using closed nests, in a montane farming area of Taiwan. We found that Asian house martins constructed dome-shaped nests in human houses that provided additional nest sites for russet sparrows, secondary cavity-nesters with greatly declining populations in Taiwan. Russet sparrows that used house martin nests had reproductive success comparable to those that used artificial nest boxes. However, Asian house martins avoided reclaiming sparrow-used nests, which reduced their available nest sites. Interestingly, our results imply that man-made structures may be used as a conservation tool to improve the breeding of the endangered russet sparrows via this facilitative interaction.</span></p>

opencc-zeroJul 2022View details →
zenodo36/100

Fig. 4 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications

Fig. 4. (continued).

opencc-by-4.0Aug 2022View details →
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Fig. 3 in The complete mitochondrial genome of Platygaster robiniae (Hymenoptera: Platygastridae): A novel tRNA secondary structure, gene rearrangements and phylogenetic implications

Fig. 3. The secondary structure of 22 tRNA in Platygaster robiniae.

opencc-by-4.0Aug 2022View details →
dryad36/100

Landscape structure, predictability of forest regeneration trajectories, and recovery rate on secondary forests

<p>Abandonment of agricultural lands promotes the global expansion of secondary forests, which are critical for preserving biodiversity and ecosystem functions and services. Such roles largely depend, however, on two essential successional attributes, trajectory and recovery rate, which are expected to depend on landscape-scale forest cover in non- linear ways. This dataset is the synthesis outcome of 22 independent databases from studies of woody plant species recovery as part of the research project entitled "Impacts of landscape structure on secondary tropical forest regeneration". This work aimed to understand the effect of landscape-level disturbance on forest regeneration, specifically through the predictability of trajectories and the recovery rate of these forests.</p> <p>Using a multiscale approach and a large vegetation dataset (843 plots, 3511 tree species) from 22 secondary forest chronosequences distributed across the Neotropics, we show that successional trajectories of woody plant species richness, stem density, and basal area are less predictable in landscapes (4-km radius) with intermediate (40-60%) forest cover than in landscapes with high (&gt;60%) forest cover. This supports theory suggesting that high spatial and environmental heterogeneity in intermediately deforested landscapes can increase the variation in key ecological factors for forest recovery (e.g. seed dispersal, seedling recruitment), increasing the uncertainty of successional trajectories. Regarding the recovery rate, only the species richness is positively related to forest cover in relatively small (1-km radius) landscapes. These findings highlight the importance of using a spatially-explicit landscape approach in restoration initiatives and suggest that these initiatives can be more effective in more forested landscapes, especially if implemented across spatial extents of 1-4 km radius. </p>

opencc-zeroDec 2022View details →
zenodo36/100

ConforMine Molecular Dynamics Data: Conformational Variability, Secondary Structure Propensities and Molecular Dynamics Simulations

<pre>This dataset contains all the data used to calculate Conformational Variability (ConVa) and Conformational Propensities as well as to train ConforMine. Each directory one level below this document contains another readme for further explanation on the contained data. The following information can be found in this dataset: </pre> <ul> <li>ConforMine_MD_training_sequences.fasta: FASTA file with the amino acid sequences of all used proteins.</li> <li>simulations (directory): Contains all the raw data derived from the MD simulations.</li> <li>ConforMine_training_MD_dihedrals (directory): Contains .xvg files with the dihedral angles of each amino acid at each step of the MD simulation.</li> <li>ConforMine_training_data_conformational_variability (directory): Contains the Conformational Variability values for all amino acids. Each file contains all ConVa values for a whole protein. The data is provided in .csv and .npy format.</li> <li>ConforMine_training_data_conformational_propensities (directory): Contains the Conformational Propensities values for all amino acids. Each file contains all propensities for a whole protein. The data is provided in .csv and .npy format.</li> </ul>

opencc-by-4.0Jan 2023View details →
dryad36/100

Data for: The influence of vegetation structure on secondary diaspore dispersal by wind

<p><span>The role of vegetation structure in relation to wind speed and diaspore attributes on secondary diaspore dispersal by wind has not </span><span>been empirically studied</span><span>. </span><span>Here, we investigated secondary dispersal by wind of diaspores placed in </span><span>12</span><span> different kinds of vegetation</span><span> and bare land</span><span>. The experiments were conducted in a wind tunnel using a range of wind speeds and diaspores that differed in mass and kind of appendages. </span><span>The explanations of wind speed, diaspore attribute</span><span>s</span><span>, vegetation coverage, life-form, vertical </span><span>pattern </span><span>and horizontal pattern for diaspore dispersal capacity were 6.67~10.40%, 16.13~20.53%, </span><span>6.227~</span><span>24.64%, 0.10%, 0.74%, and 0.10%, respectively. </span><span>Compared with wind speed and diaspore attributes, vegetation coverage contributed the most to diaspore dispersal capacity when vegetation coverage was low (</span><span>&lt;10% in our study). However</span><span>, but with a high (10-30%) coverage, vegetation coverage was the least influential factor in secondary diaspore dispersal by wind. V</span><span>egetation coverage </span><span>significantly </span><span>interact</span><span>ed with</span> <span>vegetation life-form, horizontal pattern and vertical pattern </span><span>on affecting</span><span> diaspore dispersal capacity. </span><span>Thus,</span><span> the most influential factor determining secondary diaspore dispersal by wind is vegetation coverage.</span></p>

opencc-zeroFeb 2023View details →
zenodo36/100

Nanoscale chemical characterization of secondary protein structure of F-Actin using mid-infrared photoinduced force microscopy (PiF-IR)

<p>Raw data for manuscript for special issue in Spectrochimica Acta related to ECSBM 2022</p> <p>&nbsp;</p>

opencc-by-4.0Mar 2023View details →
dryad36/100

The role of a synanthropic bird in the nest niche expansion of a secondary cavity-nester to man-made structures

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publicJul 2022View details →
dryad36/100

Landscape structure, predictability of forest regeneration trajectories, and recovery rate on secondary forests

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publicDec 2022View details →
dryad36/100

Data for: The influence of vegetation structure on secondary diaspore dispersal by wind

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publicFeb 2023View details →
dryad36/100

Forest diversity and structure in regenerating secondary forests after shifting cultivation abandonment in the Philippines uplands

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publicMay 2021View details →

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