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Figure 4: ExaminationDB Ontology class and subclass
<p>DB Mapping: a case of study<br> In order to explain how the methodology works, we analyze step by step,<br> a simple mapping on a database sample named ExaminationDB .<br> STEP 1. Seven classes are generated: assistant_teacher, course_degree,<br> examination, professor, relative, student, sustains.<br> STEP 2. Doctor and researcher are added as a set of disjoined subclasses<br> of class assistant_teacher; associate_professor and full_professor are added<br> as a set of disjoined subclasses of class professor (Figure 4).<br> STEP 3. 32 Data Properties are generated : 11 related to the primary<br> keys (named PK_NomeDominio_NomeAttributo and 21 related to the others<br> attributes and named NomeDominio_NomeAttributo. For each data type of a<br> table attribute, exists a range of values in the corresponding Data Property in the generated ontology. For example the Data Property professor_Address is<br> a string, because the attribute address of the professor table in ExaminationDb<br> is a Varchar type.<br> STEP 4. 10 Object Properties are generated . Six Object Properties are<br> related to the Foreign Keys (examinationhasFK_Cod_Course, examinationhasFK_<br> CF_PROFESSOR etc. . . ). Four Object Properties are related to the<br> class involved in disjoint relations (associate_professor, full_professor, doctor,<br> researcher), and they have the parent class as a Range and the primary key<br> as a relation key. For example we have the 4 object Properties: researcherhasPK_<br> CF, associate_professorhasPK_CF, full_professorhasPK_CF, doctorhasPK_<br> CF.<br> STEP 5. It is created a restriction having a minimum cardinality equal<br> to 1 or to 0, on each Data Property corresponding respectively to a NOT<br> NULL (avoiding the PK) and to a NULL attribute. For example we will have<br> assistant_teacher_Address min 1;<br> STEP 6. On each Data Property corresponding to a Primary Key attribute<br> of the database source, is added a restriction having cardinality exactly 1.</p>
Рис. 5. Зависимость межΔу цветом и размером цист Heterodera glycines. ГраΔации цвета цист: 1 — моΛочный, 2 — жеΛтый и светΛо-коричневый, 3 — коричневый, 4 — каштановый, 5 — темно-коричневый. Размер цист — в баΛΛах Fig. 5. Relationship between the color and size of Heterodera glycines cysts. Color gradations of cysts: 1 — milky, 2 — yellow and light brown, 3 — brown, 4 — chestnut, 5 — dark brown. The size of cysts — in classes in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions
Рис. 5. Зависимость межΔу цветом и размером цист Heterodera glycines. ГраΔации цвета цист: 1 — моΛочный, 2 — жеΛтый и светΛо-коричневый, 3 — коричневый, 4 — каштановый, 5 — темно-коричневый. Размер цист — в баΛΛах Fig. 5. Relationship between the color and size of Heterodera glycines cysts. Color gradations of cysts: 1 — milky, 2 — yellow and light brown, 3 — brown, 4 — chestnut, 5 — dark brown. The size of cysts — in classes
Рис. 4. Сезонная Δинамика размеров цист Heterodera glycines и чисΛа яиц в них. Размер цист в баΛΛах: 1 — меΛкие, 2 — среΔние, 3 — крупные Fig. 4. Seasonal dynamics of the size of Heterodera glycines cysts and the number of eggs in them. The size of cysts in classes: 1 — small, 2 — medium, 3 — large in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions
Рис. 4. Сезонная Δинамика размеров цист Heterodera glycines и чисΛа яиц в них. Размер цист в баΛΛах: 1 — меΛкие, 2 — среΔние, 3 — крупные Fig. 4. Seasonal dynamics of the size of Heterodera glycines cysts and the number of eggs in them. The size of cysts in classes: 1 — small, 2 — medium, 3 — large
Sequential Synthesis and Secondary Structure Analysis of Two Classes of Perylene Bisimide Oligomers
<p>Data to report <a title="DOI URL" href="https://doi.org/10.1021/acs.orglett.4c01928">https://doi.org/10.1021/acs.orglett.4c01928</a><a title="DOI URL" href="https://doi.org/10.1021/acs.orglett.4c01928">:</a></p> <p>An iterative step-by-step synthetic approach is employed to form perylene bisimide (PBI) oligomers with defined size by connecting the PBI units through their imide positions via a benzyl linker. The versatility of this approach was showcased by its successful implementation on two different PBI building blocks to achieve two separate series of oligomers (up to the pentamer) with modulated conformations; the one with an open random coil oligomer and the other with an H-type foldamer architecture.</p>
Annotation of the non-canonical translatome reveals that CHO cell microproteins are a new class of therapeutic antibody drug product impurity
<p>3,681 novel Chinese hamster proteoforms (derived from uORFs, ouORFs and ORFs encoded on NCBI annotated non-coding RNAs).</p>
Fig. 2 in Resource use by the facultative lepidophage Roeboides affinis (Günther, 1868): a comparison of size classes, seasons and environment types related to impoundment
Fig. 2. Medians of percentage volume of scales consumed by Roeboides affinis in the upper Tocantins river, from 1995 to 2000, in: (a) different environmental types (Lotic, n = 38, vs. Lentic, n = 52); (b) seasons (Dry, n = 25, vs. Wet, n = 68); (c) size classes 1 (n = 12), 2 (n = 38), 3 (n = 26), 4 (n = 9) and 5 (n = 5) and (d) different post-impoundment phases (Filling, n = 9, vs. Operation, n = 2) in lentic sites.
Fig. 1 in Resource use by the facultative lepidophage Roeboides affinis (Günther, 1868): a comparison of size classes, seasons and environment types related to impoundment
Fig. 1. CA ordination of 155 individuals of Roeboides affinis of two groups formed by five size classes (Group1, n = 33, and Group 2, n = 22) according to the consumption of food items (volumetric proportions) in the upper Tocantins River in two environment types (Lotic, n = 61, vs. Lentic, n = 94) related to its impoundment by the Serra da Mesa Hydroelectric Dam, from 1995 to 2000.
Fig. 3 in A report on 24 unrecorded bacterial species of Korea isolated in 2016, belonging to the orders Rhizobiales and Sphingomonadales in the class Alphaproteobacteria
Fig. 3. Neighbor-joining phylogenetic tree based on 16S rRNA gene sequences showing the relationship between the strains isolated in this study and their relatives in the Sphingomonadales of the Alphaproteobacteria. Bootstrap values (expressed as percentages of 1000 replications) over 70% are shown at nodes for neighbour-joining, maximum parsimony, and maximum likelihood methods, respectively. Filled circles and open circles indicate that the corresponding nodes were recovered by all treeing methods and by two treeing methods, respectively. Bootstrap values (>70%) are shown at nodes. Bar, 0.02 substitutions per nucleotide position.
Fig. 1 in A report on 24 unrecorded bacterial species of Korea isolated in 2016, belonging to the orders Rhizobiales and Sphingomonadales in the class Alphaproteobacteria
Fig. 1. Transmission electron micrographs of the strains isolated in this study. Strains: 1, HMF4680; 2, Gsoil 1041; 3, YC4-26; 4, 16_S3_ F7; 5, HMF4666; 6, SG2-5; 7, Gsoil 531; 8, KH7a; 9, Gsoil 3034-1; 10, 16_S4_T9; 11, CAU 1113; 12, IMCC25650; 13, IMCC25649; 14, JMS-19; 15, HMF8222; 16, HMF6028; 17, MMS16-CNU530; 18, HMF6507; 19, CAU 1116; 20, EMML2331-1; 21, Gsoil 130; 22, Gsoil 187; 23, CAU 1064; 24, IMCC25648.
Figs. 6–10. 6. Cerithium magnum Jay, 1836 in Catalog Of Recent Type Specimens In The Division Of Invertebrate Zoology, American Museum Of Natural History. V. Mollusca, Part 2 (Class Gastropoda [Exclusive Opisthobranchia And Pulmonata With Supplements To Gastropoda [Opisthobranchia], And Bivalvia
Figs. 6–10. 6. Cerithium magnum Jay, 1836 (lectotype—AMNH 56067), X 0.75. 7. Conus Bernardi and Crosse, 1861 (syntype—AMNH 47629), X 1.75. 8. Conus pseudoaustini Usticke, (holotype—AMNH 195452), X 2. 9. Cyclostoma maculosa Jay, 1839 (syntype—AMNH 56086), 10. Cyclostoma multilineata Jay, 1839 (syntype—AMNH 56087), X 2.6.
Figure 2 in Communities of the Bidentetea class of small coastal river valleys of the Western Pomerania (Poland)
Figure 2. The numerical classification of relevés from rivers of the Wałcz Plain – dendrogram (1-68 – numbers of relevés; A – comm. with Polygonum minus; B – Chenopodietum rubri Timar 1947; C – Bidentetum cernui Kobendza 1948; Da-Df – Bidenti-Polygonetum hydropiperis (Miljan 1933) Lohmeyer in R.Tx. 1950 nom invers).
Рис. 5. Варианты преΑсказанной Αоменной структуры скавенΑжер-рецепторов гемоцитов моΛΛюсков Planorbarius corneus. Сокращения (зΑесь и ΑаΛее): SR — богатый цистеином Αомен скавенΑжер-рецептора, Filament — Αомен промежуточного фиΛамента, TSP1 — повторы тромбоспонΑина типа 1, KR — крингΛ-Αомен, LDLa — Αомен рецептора Λипопротеинов низкой пΛотности кΛасса А Fig. 5. Variants of the predicted domain structure of scavenger receptors from hemocytes of Planorbarius corneus molluscs. Abbreviations (here and in what follows): SR — scavenger receptor Cys-rich domain, Filament — intermediate filament protein, TSP1 — thrombospondin type 1 repeats, KR — kringle domain, LDLa — low-density lipoprotein receptor domain class A in Pathogen recognition molecules from hemocytes of Planorbarius corneus molluscs (Planorbidae, Pulmonata)
Рис. 5. Варианты преΑсказанной Αоменной структуры скавенΑжер-рецепторов гемоцитов моΛΛюсков Planorbarius corneus. Сокращения (зΑесь и ΑаΛее): SR — богатый цистеином Αомен скавенΑжер-рецептора, Filament — Αомен промежуточного фиΛамента, TSP1 — повторы тромбоспонΑина типа 1, KR — крингΛ-Αомен, LDLa — Αомен рецептора Λипопротеинов низкой пΛотности кΛасса А Fig. 5. Variants of the predicted domain structure of scavenger receptors from hemocytes of Planorbarius corneus molluscs. Abbreviations (here and in what follows): SR — scavenger receptor Cys-rich domain, Filament — intermediate filament protein, TSP1 — thrombospondin type 1 repeats, KR — kringle domain, LDLa — low-density lipoprotein receptor domain class A
Fig. 1 in A report on 30 unrecorded bacteria species in Korea belonging to the classes Betaproteobacteria and Gammaproteobacteria in 2021
Fig. 1. Transmission electron micrographs of cells of the strains belonging to the Betaproteobacteria and Gammaproteobacteria. The strains were cultured at their optimal growth conditions. Strain: 1, HMG1432; 2, HMG1944; 3, HMG2081; 4, HMG5310; 5, SATFR7; 6, ATS74; 7, PS9; 8, 18JY64; 9, BT33; 10, MMS21YDR2; 11, CAU 1658; 12, 16_SB_L4; 13, G12; 14, CAU 1657; 15, 15G113; 16, CAU 1650; 17, MMS21M35; 18, CAU 1655; 19, 17_H6_M9; 20, GJ5111; 21, G510; 22, CAU 1666; 23, SATFR3; 24, AMTFM1; 25, AMTFM15; 26, AMTFR2; 27, DSTFM2; 28, BT758; 29, JHKTFM108; 30, DSTFM15.
Fig. 3 in A report on 30 unrecorded bacteria species in Korea belonging to the classes Betaproteobacteria and Gammaproteobacteria in 2021
Fig. 3. Neighborjoining (NJ) phylogenetic tree based on 16S rRNA gene sequences, showing the relationships between the strains identified in this study and their relatives of the orders Aeromonadales, Alteromonadales, Cellvibrionales, Enterobacterales, Lysobacterales, Moraxellales, Oceanospirillales, Pseudomonadales, and Vibrionales in the class Gammaproteobacteria. Black dots indicate that the corresponding nodes were also recovered in the trees generated using the maximum likelihood (ML) and maximum parsimony (MP) algorithms. Bootstrap values (>70%) based on 1,000 replications are indicated at branch points (NJ/ML/MP). The scale bar represents a 0.02 nucleotide sequence divergence.
Fig. 2 in A report on 30 unrecorded bacteria species in Korea belonging to the classes Betaproteobacteria and Gammaproteobacteria in 2021
Fig. 2. Neighborjoining (NJ) phylogenetic tree based on 16S rRNA gene sequences, showing the relationships between the strains identified in this study and their relatives of the order Burkholderiales in the class Betaproteobacteira. Black dots indicate that the corresponding nodes were also recovered in the trees generated using the maximum likelihood (ML) and maximum parsimony (MP) algorithms. Bootstrap values (>70%) based on 1,000 replications are indicated at branch points (NJ/ML/MP). The scale bar represents a 0.02 nucleotide sequence divergence.
Fig. 3 in A report of 31 unrecorded bacterial species in South Korea belonging to the class Gammaproteobacteria
Fig. 3. Neighbor-joining phylogenetic tree, based on 16S rRNA gene sequences, showing the relationships between the strains isolated in this study and their relatives of the order Enterobacteriales in the class Gammaproteobacteria. Bootstrap values (>50%) are shown at branching points. Filled circles indicate that the corresponding nodes were also recovered in the trees generated with the maximum-likelihood and maximum-parsimony algorithms, while open circles indicate that the corresponding nodes were also recovered in the tree generated with one of these algorithms. Bar, 0.01 substitutions per nucleotide position.
Fig. 2 in A report of 31 unrecorded bacterial species in South Korea belonging to the class Gammaproteobacteria
Fig. 2. Neighbor-joining phylogenetic tree, based on 16S rRNA gene sequences, showing the relationships between the strains isolated in this study and their relatives of the order Pseudomonadales in the class Gammaproteobacteria. Bootstrap values (>50%) are shown at branching points. Filled circles indicate that the corresponding nodes were also recovered in the trees generated with the maximum-likelihood and maximum-parsimony algorithms, while open circles indicate that the corresponding nodes were also recovered in the tree generated with one of these algorithms. Bar, 0.01 substitutions per nucleotide position.
Fig. 4 in A report of 31 unrecorded bacterial species in South Korea belonging to the class Gammaproteobacteria
Fig. 4. Neighbor-joining phylogenetic tree, based on 16S rRNA gene sequences, showing the relationships between the strains isolated in this study and their relatives of the class Gammaproteobacteria. Bootstrap values (>50%) are shown at branching points. Filled circles indicate that the corresponding nodes were also recovered in the trees generated with the maximum-likelihood and maximum-parsimony algorithms. Bar, 0.01 substitutions per nucleotide position.
Fig. 1 in A report of 31 unrecorded bacterial species in South Korea belonging to the class Gammaproteobacteria
Fig. 1. Transmission electron micrographs or scanning electron micrographs of cells of the strains isolated in this study. Strains: 1, DT1-03; 2, DT1-04; 3, DT1-05; 4, DT5-05; 5, ST6-03; 6, DR3-01; 7, SR3-03; 8, SR4-03; 9, SR6-02; 10, Gsoil 852; 11, MBM1; 12, MDY2F18; 13, MBB2-1; 14, JJ9010; 15, IMCC1859; 16, IMCC20105; 17, IMCC20160; 18, IMCC20164; 19, IMCC20180; 20, MWS24; 21, NMWL17; 22, SD19; 23, B-12; 24, SJ3-2; 25, JW17; 26, HME9287; 27, HME9331; 28, HME9414; 29, HME9429; 30, WS85; 31, WW126.
Fig. 4 in A report on 33 unrecorded bacterial species of Korea isolated in 2014, belonging to the class Gammaproteobacteria
Fig. 4. Neighbor-joining phylogenetic tree, based on 16S rRNA gene sequences, showing the phylogenetic relationship between the strains isolated in this study and their relatives of the order Pseudomonadales in the class Gammaproteobacteria. Sphingopyxis macrogoltabida IFO 15033T (D13723) was used as an outgroup. Bootstrap values (>70%) are shown above nodes for the neighbor-joining. Scale bar: 0.02 changes per nucleotide.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.