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opencc-by-4.0Dec 2023View details →

Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2) in Structure and dynamics of the taxocenes of shrews in different habitats of the Norsky nature reserve

Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2)

opencc-by-4.0Dec 2023View details →

Рис. 2. Структура Αоминирования в таксоценах земΛероек (справа) и UPGMA ΑенΑрограмма схоΑства (сΛева) выборок, соответствующих основным типам местообитаний (L_1–L_7) земΛероек в Норском заповеΑнике по резуΛьтатам мониторинга 2017–2022. Расшифровка коΑов учетных пΛощаΑок преΑставΛена на рис. 1. 1 — S. caecutiens, 2 — S. roboratus, 3 — S. daphaenodon, 4 — S. isodon, 5 — S. minutissimus, 6 — S. gracillimus, 7 — S. tundrensis in Structure and dynamics of the taxocenes of shrews in different habitats of the Norsky nature reserve

Рис. 2. Структура Αоминирования в таксоценах земΛероек (справа) и UPGMA ΑенΑрограмма схоΑства (сΛева) выборок, соответствующих основным типам местообитаний (L_1–L_7) земΛероек в Норском заповеΑнике по резуΛьтатам мониторинга 2017–2022. Расшифровка коΑов учетных пΛощаΑок преΑставΛена на рис. 1. 1 — S. caecutiens, 2 — S. roboratus, 3 — S. daphaenodon, 4 — S. isodon, 5 — S. minutissimus, 6 — S. gracillimus, 7 — S. tundrensis

opencc-by-4.0Dec 2022View details →

Рис. 3. Возрастная Δинамика относитеΛьных приростов ΔΛины (А) и массы теΛа (А) бурого морского петушка Alectrias alectrolophus из разных районов Тауйской губы Охотского моря Fig. 3. Age-related dynamics of relative gains in length (A) and body weight (A) of stone cockscomb Alectrias alectrolophus from different regions of Taui Bay, the Sea of Okhotsk in Size-age structure, growth, and feeding of stone cockscomb Alectrias alectrolophus (Stichaeidae) from different areas of Taui Bay, the Sea of Okhotsk

Рис. 3. Возрастная Δинамика относитеΛьных приростов ΔΛины (А) и массы теΛа (А) бурого морского петушка Alectrias alectrolophus из разных районов Тауйской губы Охотского моря Fig. 3. Age-related dynamics of relative gains in length (A) and body weight (A) of stone cockscomb Alectrias alectrolophus from different regions of Taui Bay, the Sea of Okhotsk

opencc-by-4.0Apr 2018View details →

Using the Genetic Algorithm for the Optimization of Dynamic School Bus Routing Problem-Figure 4. Example of a chromosome structure with permutation coding

Each chromosome found in the population formed in the GA is structurally an equal-length coded series. The chromosomes are made of genes. For coding purposes, binary, permutation, and value coding methods are widely used. In the travelling salesman or other similar VRPs, permutation coding technique is preferred over the other techniques. Using the permutation coding technique, each chromosome found in the population is expressed in terms of the numbers of each stop to be followed in the route, as shown in Figure 4.

opencc-by-sa-4.0Aug 2018View details →

Structural dynamics of the E6AP/UBE3A-E6-p53 enzyme-substrate complex

Deregulation of the ubiquitin ligase E6AP is causally linked to the development of human disease, including cervical cancer. In complex with the E6 oncoprotein of human papillomaviruses, E6AP targets the tumor suppressor p53 for degradation, thereby contributing to carcinogenesis. Moreover, E6 acts as a potent activator of E6AP by a yet unknown mechanism. However, structural information explaining how the E6AP-E6-p53 enzyme-substrate complex is assembled, and how E6 stimulates E6AP, is largely missing. We therefore developed and applied different approaches in structural mass spectrometry to show that binding of E6 induces conformational rearrangements in E6AP, which result in the positioning of E6 and p53 in the immediate vicinity of the catalytic centre of E6AP. Our data provides structural and functional insights into the dynamics of the full-length E6AP-E6-p53 enzyme-substrate complex and reveals how E6 can both stimulate the ubiquitin ligase activity of E6AP and facilitate the transfer of ubiquitin from E6AP onto p53.

Figure 4 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China

Figure 4. Bayesian tree based on mitochondrial haplotypes (1053 bp, selected model of HKY+I+G). It exhibits the phylogenetic relationships of silver pheasant, and three species (L. hatinhensis, L. leucomelanos, and L. swinhoii) are noticeable outgroups. Above branches there are numbers indicating Bayesian posterior probabilities, whereas below branches there are bootstrap values produced by ML. Each colored line represents a geographic population, while the line in black represents the shared haplotype.

Figure 3 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China

Figure 3. mtDNA MJN for silver pheasant. Circle size represents proportion of haplotype. Circles with single color indicate a private haplotype, whereas circles with two or more colors represent a shared haplotype.

Figure 1 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China

Figure 1. According to geodistance and topographic characters, we sorted sampling sites into geographic populations. The sampling sites including 7 provinces: Sichuan, Anhui, Jiangxi, Fujian, Zhejiang, Hubei, and Hunan. The abbreviation are as follows: Sichuan (SC), Anhui (AH), Jiangxi (JX), Fujian (FJ), Zhejiang (ZJ), Hubei (HB), Hunan (HN).

Figure 2 in Genetic structure and population dynamics of the silver pheasant (Lophura nycthemera) in southern China

Figure 2. Bayesian skyline plot of whole population of silver pheasant. The expansion time was computed by tau = 2µkt. The solid line means the estimated average effective population size and the dashed line represents 95% confidence interval.

opencc-by-4.0Jul 2024View details →

Data Supplement for "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations"

Data set containing the molecular dynamics simulation data used for the journal article "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations" (Andreas Thum, Diddo Diddens, Andreas Heuer, J. Phys. Chem. C 2021, 125, 25392−25403, <a href="https://doi.org/10.1021/acs.jpcc.1c07751">https://doi.org/10.1021/acs.jpcc.1c07751</a>).

opencc-by-4.0Sep 2024View details →

Datasets and scripts for: Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope

The folder contains raw datasets (.ptu files) together with scripts and relevant results to reproduce the figures' plots of: "Single-Molecule Dynamic Structural Biology with Vertically Arranged DNA on a Fluorescence Microscope".

opencc-by-4.0Oct 2024View details →

Data from: Personality and social network structure influence cooperative dynamics across canid species

In canids, cooperative behaviour occurs in many scenarios. However, most studies focus on single-species observations, not accounting for variation beyond the species-level. We modelled cooperative behaviour using Eigenvalue centrality as well as boldness combined with biological traits such as kinship, sex, age, mating system and foraging strategy in multiple canid species with Bayesian inference, Tukey HSD and distance correlation.

openmit-licenseOct 2024View details →

Gaussian16 data for "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning"

This is the Gaussian 16 input and corresponding output, which was used as input into the machine learning presented in the paper titled "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning". This upload is required before submission of the paper. The 1001 and 100 snapshots from different extractions are preserved in separated directories. Each snapshot directory <code>*_snapshot</code> has the initial GROMACS snapshot <code>test_*.pdb</code> , the geometry after truncating the solvation shell in various formats, the Gaussian16 input, qsub input and the output directory <code>*.1</code> with a JobID number assigned by qsub. The output directory has the standard output from Gaussian in a <code>.log</code> file and <code>grep</code>ed output from the <code>.fchk</code>  file in <code>*.out</code> .

opencc-by-4.0Oct 2024View details →

Initial Structures of PKM1/M2 proteins for AMOEBA Molecular Dynamics studies (xyz Tinker format)

Here are presented our initial structures of PKM1/M2 (solvated and neutralized) for the different states to initiate molecular dynamics in AMOEBA force field. Those are represented in xyz Tinker format and come from their respectives PDB crystal structure after extraction of the unwanted ligands : 3SRF for PKM1, 1ZJH for monomer PKM2, 6B6U for dimer PKM2, 3SRH for free-tetramer PKM2, 3SRD for tetramer PKM2 bound to FBP, 3U2Z for tetramer PKM2 bound to TEPP-46.

opencc-by-4.0Nov 2024View details →

AlphaFold2-Based Characterization of Apo and Holo Protein Structures and Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics and Ligand-Induced Conformational Changes

Proteins often exist in multiple conformational states, influenced by the binding of ligands or substrates. The study of these states, particularly the apo (unbound) and holo (ligand-bound) forms, is crucial for understanding protein function, dynamics, and interactions. In the current study, we use AlphaFold2 that combines randomized  alanine  sequence masking  with shallow multiple sequence alignment  subsampling to expand the conformational diversity of the predicted structural  ensembles and   capture conformational changes between apo and holo protein forms. Using several well-established datasets of  structurally diverse apo-holo protein pairs, the proposed approach enables  robust predictions of apo and holo structures and conformational ensembles, while also displaying notably similar dynamics distributions. These observations are consistent with  the view  that the intrinsic dynamics of allosteric proteins is defined by the structural topology of the fold and favors conserved conformational motions driven by soft modes among orthologs. We also found  a significant correlation between conformational flexibility and  AlphaFold2 metric of statistical significance pLDDT for the apo-holo pairs in which ligand binding induced local moderate conformational changes. For apo-holo pairs exhibiting larger structural changes, this relationship  becomes nonlinear, reflecting inability of AlphaFold2 confidence metrics to identify high energy functional conformations. Our findings support the notion that AlphaFold2 approaches can yield reasonable accuracy in predicting minor conformational adjustments between apo and holo states, especially for proteins with  moderate localized changes upon ligand binding. However, for large, hinge-like domain movements, AF2 tends to predict the most stable domain orientation which is typically the apo form rather than the full range of functional conformations characteristic of the holo ensemble. These results indicate that modeling of multiple functional states of proteins may require more accurate detection of flexible region conformations and cannot solely rely on the pLDDT metric as the major determinant of the prediction accuracy in reproducing functional conformational ensembles.

opencc-by-4.0Jul 2021View details →

Amorphous Niobium Oxide Structures Calculated from First Principles using Density Functional Theory and Molecular Dynamics

The dataset contains fifteen different amorphous niobium oxide structures. Nine of the structures have the same stoichiometry as Nb2O5. The other six are defect structures containing 1 or 2 oxygen vacancies, or 1 or 2 interstitial oxygens, or 1 Nb vacancy. Each of the structure files is in the VASP POSCAR file format. Each structure was created using ab-initio molecular dynamics at 5000~K to liquidate the structure, then snapshots of the structure were taken every 2 ps, and geometry optimizations were performed on each individual snapshot. The naming convention is relatively simple: 'conf_x_POSCAR' is a stoichiometric POSCAR, and 'conf_x_oadd1_POSCAR' is a defect structure originating from structure 'x' with a single oxygen interstitial. The defect labels correspond to 1 oxygen interstitial (oadd1), 2 oxygen interstitials (oadd2), 1 oxygen vacancy (ovac1), 2 separated oxygen vacancies (ovac2), 2 nearest neighbor oxygen vacancies (ovac2nn), and 1 Nb vacancy (nbvac).

Figure 2 in Population dynamics, age structure and sex ratio of the bromeliad-dwelling jumping spider, Psecas chapoda (Salticidae)

Figure 2. Mean number (¡SE) of Psecas chapoda per Bromelia balansae with no inflorescence, from May 1998 to April 2000 (N53516 spiders).

Figure 1 in Population dynamics, age structure and sex ratio of the bromeliad-dwelling jumping spider, Psecas chapoda (Salticidae)

Figure 1. Fluctuations in the number of Psecas chapoda and egg sacs (log) on bromeliads with and without inflorescence, and the frequency (%) of bromeliads in bloom (with inflorescence or infrutescence) between May 1998 and April 2000 (N53516 spiders and 314 egg sacs).

Figure 5 in Population dynamics, age structure and sex ratio of the bromeliad-dwelling jumping spider, Psecas chapoda (Salticidae)

Figure 5. Mean number (¡SE) of spiders Psecas chapoda on bromeliads that produced inflorescence between August and December and on bromeliads that did not produce inflorescence until December, in 1998 (A) and 1999 (B). The frequency (%) of bromeliads that bloomed up to December is also shown.

Figure 4 in Population dynamics, age structure and sex ratio of the bromeliad-dwelling jumping spider, Psecas chapoda (Salticidae)

Figure 4. Phenogram of the Psecas chapoda population on plants of Bromelia balansae without inflorescence, from May 1998 to April 2000 (N53516 spiders).