Hasil untuk "Maps"

M. Kanehisa, Miho Furumichi, Yoko Sato et al.

Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.

Stephan Greiner, Pascal Lehwark, R. Bock

OGDRAW has become the standard tool for displaying maps of organellar genomes it converts GenBank entries into graphical maps a new version with improved functionality has been released Abstract Organellar (plastid and mitochondrial) genomes play an important role in resolving phylogenetic relationships, and next-generation sequencing technologies have led to a burst in their availability. The ongoing massive sequencing efforts require software tools for routine assembly and annotation of organellar genomes as well as their display as physical maps. OrganellarGenomeDRAW (OGDRAW) has become the standard tool to draw graphical maps of plastid and mitochondrial genomes. Here were present a new version of OGDRAW equipped with a new front end. Besides several new features, OGDRAW has now access to a local copy of the organelle genome database of the NCBI RefSeq project. Together with batch processing of (multi-)GenBank files, this enables the user to easily visualize large sets of organellar genomes spanning entire taxonomic clades. The new OGDRAW server can be accessed at https://chlorobox.mpimp-golm.mpg.de/OGDraw.html.

F. Wolf, F. Hamey, M. Plass et al.

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions (https://github.com/theislab/paga). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.

E. Riehl, Dominic R. Verity

Evan M. Gordon, Timothy O. Laumann, Babatunde Adeyemo et al.

Ben G. Holt, J. Lessard, M. Borregaard et al.

Maxim Imakaev, G. Fudenberg, R. McCord et al.

Extracting biologically meaningful information from chromosomal interactions obtained with genome-wide chromosome conformation capture (3C) analyses requires the elimination of systematic biases. We present a computational pipeline that integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. We validate this ICE (iterative correction and eigenvector decomposition) technique on published data obtained by the high-throughput 3C method Hi-C, and we demonstrate that eigenvector decomposition of the obtained maps provides insights into local chromatin states, global patterns of chromosomal interactions, and the conserved organization of human and mouse chromosomes.

Faranak Farzan, M. Eldaief, R. Buckner et al.

Chandraprakash Giri, E. Ochieng, L. Tieszen et al.

Maryam Mirzakhani

K. Petersen, R. Feldt, Shahid Mujtaba et al.

BACKGROUND: A software engineering systematic map is a defined method to build a classification scheme and structure a software engineering field of interest. The analysis of results focuses on frequencies of publications for categories within the scheme. Thereby, the coverage of the research field can be determined. Different facets of the scheme can also be combined to answer more specific research questions. OBJECTIVE: We describe how to conduct a systematic mapping study in software engineering and provide guidelines. We also compare systematic maps and systematic reviews to clarify how to chose between them. This comparison leads to a set of guidelines for systematic maps. METHOD: We have defined a systematic mapping process and applied it to complete a systematic mapping study. Furthermore, we compare systematic maps with systematic reviews by systematically analyzing existing systematic reviews. RESULTS: We describe a process for software engineering systematic mapping studies and compare it to systematic reviews. Based on this, guidelines for conducting systematic maps are defined. CONCLUSIONS: Systematic maps and reviews are different in terms of goals, breadth, validity issues and implications. Thus, they should be used complementarily and require different methods (e.g., for analysis).

Ashbindu Singh

J. Andersson, S. Skare, J. Ashburner

M. Jakobson

B. Tversky

Manuel G. Pinedo-Cuba, José M. Caicedo-Roque, Jessica Padilla-Pantoja et al.

Magnetic shape memory alloys have attracted considerable attention due to their multifunctional properties. Among these materials, Ni-Mn-Ga alloys are distinguished by their ability to achieve up to 10% strain when exposed to a magnetic field, a characteristic predominantly observed in single-crystal samples. Consequently, it is essential to develop nanomaterials with a crystal structure closely resembling that of a single crystal. In this study, an epitaxial Ni-Mn-Ga thin film was fabricated using Pulsed Laser Deposition on an Al₂O₃ <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mn>11</mn><mover accent="true"><mn>2</mn><mo stretchy="false">¯</mo></mover><mn>0</mn><mo>)</mo></mrow></semantics></math></inline-formula> single-crystal substrate. The crystal structure was characterised through X-ray diffraction methodologies, such as symmetrical <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mi>θ</mi><mo>−</mo><mi>ω</mi></mrow></semantics></math></inline-formula> scans, pole figures, and reciprocal space maps. The results indicated that the sample was mainly in a slightly distorted cubic austenite phase, and some incipient martensite phase also appeared. A detailed microstructural analysis, performed by transmission electron microscopy, confirmed that certain regions of the sample exhibited an incipient transformation to the martensite phase. Regions closer to the substrate retained the austenite phase, suggesting that the constraint imposed by the substrate inhibits the phase transition. These results indicate that it is possible to grow high crystalline quality thin films of Ni-Mn-Ga by Pulsed Laser Deposition.

Behdad Sadeghi, Rahmatollah Gholipour, Mojtaba Amiri et al.

Objective This study was conducted with the goal of designing a policy-making model for sports in Iran, with a focus on the development of 'sport for all'. In terms of purpose, this study is classified as applied research, as it encompasses practical aspects for various organizations related to sports and health, in addition to providing awareness and scientific insights. Furthermore, this research is exploratory in nature, as it aims to design a model on a novel and innovative topic. Methods A mixed qualitative-quantitative method was employed in this study. The qualitative component was conducted using a situation analysis approach, which is one of the methods of grounded theory. The qualitative research involved interviewing experts; thus, 12 experts in the fields of policy making and sport management were interviewed. These experts were either professors or managers of organizations related to sports, possessing over a decade of executive and decision-making experience. Sampling was carried out using targeted and snowball methods. The quantitative section utilized interpretative structural modeling, an approach based on expert opinions, effective for exploring qualitative variables with mutual effects at various levels of importance. Results After an in-depth examination of the interviews and the data obtained, each interview was analyzed individually to extract initial codes. Subsequently, concepts and categories were developed. Messy situational maps, ordered situational maps, and social worlds/arenas maps were identified. The primary categories of the sport policy-making model in Iran for the development of 'sport for all' include contextual factors, mediating factors, role players and influential institutions, executive requirements, environmental complexities, risks, legal problems, external organizational factors, costs and expenses, and interorganizational challenges. With the aid of interpretive structural modeling, conceptual modeling was conducted. Role players and influential institutions emerged as the most significant factors in Iran's sport policy-making process, possessing the highest influence and the least dependence compared to other factors. Conclusion Given that 'sport for all' should be elevated to the level of the country's macro policies, and its development and progress should be approached as a complex issue, the policy for the development of 'sport for all' becomes especially important. Policymakers should give it significant attention. Role players and influential institutions in Iran's sports policy-making process require substantial coordination due to their numerous connections and conflicts. In Iran, 'sport for all' and organized recreation have received limited attention, and currently, there is no mechanism for monitoring sports policies and their continuous implementation. Therefore, it is recommended to implement a national physical activity monitoring plan based on a comprehensive and electronic system. Since the involvement of managers and executives, as well as their cooperation with policymakers in the policy formation process, is crucial, policymakers should be as involved as possible in the implementation process. Additionally, conditions should be facilitated to enable the private sector to effectively engage in this field.

Berhane Nugusse Zereay, Sándor Kálvin, György Juhász et al.

We developed and applied a new calibration method to make more accurate measurements with our multi-color ellipsometric mapping tool made from cheap parts. Ellipsometry is an optical technique that measures the relative change in the polarization state of the measurement beam induced by reflection from or transmission through a sample. During conventional ellipsometric measurement, the data collection is relatively slow and measures one spot at a time, so mapping needs a long time compared with our new optical mapping equipment made by an ordinary color LED monitor and a polarization-sensitive camera. The angle of incidence and the incident polarization state is varied point by point, so a special optical calibration method is needed. Three SiO₂ samples with different thicknesses were used for the point-by-point determination of the angle of incidence and rho (ρ) corrections. After the calibration, another SiO₂ sample was measured and analyzed using the calibrated corrections; further, this sample was independently measured using a conventional spectroscopic ellipsometer. The difference between the two measured thickness maps is less than 1 nm. Our optical mapping tool made from cheap parts is faster and covers wider area samples relative to conventional ellipsometers, and these correction enhancements further demonstrate its performance.

Baohua Yang, Runchao Chen, Zhiwei Gao et al.

Wheat is one of the important food crops in the world, and the stability and growth of wheat production have a decisive impact on global food security and economic prosperity. Wheat counting is of great significance for agricultural management, yield prediction and resource allocation. Research shows that the wheat ear counting method based on deep learning has achieved remarkable results and the model accuracy is high. However, the complex background of wheat fields, dense wheat ears, small wheat ear targets, and different sizes of wheat ears make the accurate positioning and counting of wheat ears still face great challenges. To this end, an automatic positioning and counting method of wheat ears based on FIDMT-GhostNet (focal inverse distance transform maps - GhostNet) is proposed. Firstly, a lightweight wheat ear counting network using GhostNet as the feature extraction network is proposed, aiming to obtain multi-scale wheat ear features. Secondly, in view of the difficulty in counting caused by dense wheat ears, the point annotation-based network FIDMT (focal inverse distance transform maps) is introduced as a baseline network to improve counting accuracy. Furthermore, to address the problem of less feature information caused by the small ear of wheat target, a dense upsampling convolution module is introduced to improve the resolution of the image and extract more detailed information. Finally, to overcome background noise or wheat ear interference, a local maximum value detection strategy is designed to realize automatic processing of wheat ear counting. To verify the effectiveness of the FIDMT-GhostNet model, the constructed wheat image data sets including WEC, WEDD and GWHD were used for training and testing. Experimental results show that the accuracy of the wheat ear counting model reaches 0.9145, and the model parameters reach 8.42M, indicating that the model FIDMT-GhostNet proposed in this study has good performance.

Ade Rifqy Setyawan, Lya Hulliyatus Suadaa, Budi Yuniarto

Tourism is one of the business fields affected by the Covid-19 pandemic. The decline in the number of tourists, both domestic and foreign, has resulted in the contribution of the tourism business sector to Indonesia's GDP decreasing. The government is now preparing plans to restore and improve tourism in tourist destination areas, one of which is DKI Jakarta in order to increase visits by domestic and foreign tourists. In achieving these goals, this study propose to utilize reviews about tourist attractions in DKI Jakarta from Google Maps and extract public opinion by conducting aspect-based sentiment analysis. Multi-label classification is a common method that is often used in aspect-based sentiment analysis. However, the multi-label approach has limited flexibility in the aspects used. One alternative method that can be used is an adaptive aspect classification method which is more flexible if there are additional new aspects used. This research aims to automate sentiment classification of tourist reviews for each aspect by developing an aspect level sentiment analysis model with an adaptive aspect classification method which will be compared with multi-label classification as a baseline method. The models used in both methods are transfer learning IndoBERT. The adaptive aspect classification method with aspect level sentiment analysis has better performance in comparison to baseline method multi-label classification with accuracy values and F1-score respectively 0.90394 and 0.71504.