TaxaTarget: Fast, Sensitive, and Precise Classification of Microeukaryotes in Metagenomic Data

BackgroundMicrobial eukaryotes are nearly ubiquitous in microbiomes on Earth and contribute to many integral ecological functions. Metagenomics is a proven tool for studying the microbial diversity, functions, and ecology of microbiomes, but has been underutilized for microeukaryotes due to the computational challenges they present. For taxonomic classification, the use of a eukaryotic marker gene database can improve the computational efficiency, precision and sensitivity. However, state-of-the-art tools which use marker gene databases implement universal thresholds for classification rather than dynamically learning the thresholds from the database structure, impacting the accuracy of the classification process.ResultsHere we introduce taxaTarget, a method for the taxonomic classification of microeukaryotes in metagenomic data. Using a database of eukaryotic marker genes and a supervised learning approach for training, we learned the discriminatory power and classification thresholds for each 20 amino acid region of each marker gene in our database. This approach provided improved sensitivity and precision compared to other state-of-the-art approaches, with rapid runtimes and low memory usage. Additionally, taxaTarget was better able to detect the presence of multiple closely related species as well as species with no representative sequences in the database. One of the greatest challenges faced during the development of taxaTarget was the general sparsity of available sequences for microeukaryotes. Several algorithms were implemented, including threshold padding, which effectively handled the missing training data and reduced classification errors. Using taxaTarget on metagenomes from human fecal microbiomes, a broader range of genera were detected, including multiple parasites that the other tested tools missed.ConclusionData-driven methods for learning classification thresholds from the structure of an input database can provide granular information about the discriminatory power of the sequences and improve the sensitivity and precision of classification. These methods will help facilitate a more comprehensive analysis of metagenomic data and expand our knowledge about the diverse eukaryotes in microbial communities.

A3D Database: Structure-based Protein Aggregation Predictions for the Human Proteome

Motivation: Protein aggregation is associated with highly debilitating human disorders and constitutes a major bottleneck for producing therapeutic proteins. Our knowledge of the human protein structures repertoire has dramatically increased with the recent development of the AlphaFold (AF) deep-learning method. This structural information can be used to understand better protein aggregation properties and the rational design of protein solubility. This article uses the Aggrescan3D (A3D) tool to compute the structure-based aggregation predictions for the human proteome and make the predictions available in a database form. Results: Here, we present the A3D Database, in which we analyze the AF-predicted human protein structures (for over 17 thousand non-membrane proteins) in terms of their aggregation properties using the A3D tool. Each entry of the A3D Database provides a detailed analysis of the structure-based aggregation propensity computed with A3D. The A3D Database implements simple but useful graphical tools for visualizing and interpreting protein structure datasets. We discuss case studies illustrating how the database could be used to analyze physiologically relevant proteins. Furthermore, the database enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. Availability and implementation: A3D Database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome

<i>dh2loop</i> 1.0: an open-source Python library for automated processing and classification of geological logs

A huge amount of legacy drilling data is available in geological survey but cannot be used directly as they are compiled and recorded in an unstructured textual form and using different formats depending on the database structure, company, logging geologist, investigation method, investigated materials and/or drilling campaign. They are subjective and plagued by uncertainty as they are likely to have been conducted by tens to hundreds of geologists, all of whom would have their own personal biases. dh2loop (https://github.com/Loop3D/dh2loop, last access: 30 September 2021​​​​​​​) is an open-source Python library for extracting and standardizing geologic drill hole data and exporting them into readily importable interval tables (collar, survey, lithology). In this contribution, we extract, process and classify lithological logs from the Geological Survey of Western Australia (GSWA) Mineral Exploration Reports (WAMEX) database in the Yalgoo–Singleton greenstone belt (YSGB) region. The contribution also addresses the subjective nature and variability of the nomenclature of lithological descriptions within and across different drilling campaigns by using thesauri and fuzzy string matching. For this study case, 86 % of the extracted lithology data is successfully matched to lithologies in the thesauri. Since this process can be tedious, we attempted to test the string matching with the comments, which resulted in a matching rate of 16 % (7870 successfully matched records out of 47 823 records). The standardized lithological data are then classified into multi-level groupings that can be used to systematically upscale and downscale drill hole data inputs for multiscale 3D geological modelling. dh2loop formats legacy data bridging the gap between utilization and maximization of legacy drill hole data and drill hole analysis functionalities available in existing Python libraries (lasio, welly, striplog).

A Location Management Strategy for Satellite Internet Constellation

Satellites are currently the most effective means to achieve seamless global coverage of the Internet. Due to the frequent beam switching caused by the high-speed movement of satellites, it is too expensive to directly apply the location management strategy in the terrestrial network to the satellite Internet constellation (SIC). To build a web browsing platform based on satellite Internet, it is necessary to display the location of satellites and terminals in real time. For this reason, this paper proposes the location management strategy of SIC. It uses the characteristics of large and periodic satellite beam coverage in a certain period of time, redesigns the location management database structure, location registration mechanism and call delivery mechanism, and analyses and simulates the bit cost of location management. The result proves that compared with the traditional strategy, this strategy greatly reduces the cost of SIC.

Chinese environmentally extended input-output database for 2017 and 2018

Environmental footprint analyses for China have gained sustained attention in the literature, which rely on quality EEIO databases based on benchmark input-output (IO) tables. The Chinese environmentally extended input-output (CEEIO) database series provide publically available EEIO databases for China for 1992, 1997, 2002, 2007, and 2012 with consistent and transparent data sources and database structure. Based on the latest benchmark IO tables for China for 2017 and 2018, here we develop the corresponding 2017 and 2018 CEEIO databases following the same method used to develop previous CEEIO databases. The 2017 and 2018 CEEIO databases cover 44 and 28 types of environmental pressures, respectively, and consider multiple sector classifications including ones consistent with previous CEEIO databases and ones following the 2017 China’s national economy industry classification standard. A notable improvement in the 2017 and 2018 CEEIO databases is the comprehensive inclusion of CO2 emissions from additional industrial processes. This work provides a consistent update of the CEEIO database and enables a wide range of timely environmental footprint analyses related to China.

Designing a database model of district-level land use planning with community consultation in Vung Tau city, Ba Ria - Vung Tau province

Nowadays, building a land database and land use planning database is an indispensable requirement, especially for a seaport city as Vung Tau city (Ba Ria - Vung Tau province) where there are complex land fluctuations. Accordingly, a complete land use planning database with the participation of community will contribute to connecting planners, managers and people, and increase the publicity, transparency and feasibility of land use planning options. The study designed a database model of land use planning with the community consultation for Vung Tau city in accordance with the land data standards of Circular No. 75/2015/TT-BTNMT. Based on the designed model, a set of land use planning database with high accuracy was created and it was in line with the data standards of the Ministry of Natural Resources and Environment and the designed database model. This database structure contained 22 spatial data tables on ArcGIS and 8 attribute data tables (with the community consultation) on Microsoft SQL Server. Finally, we successfully used the VBDLIS software to build the land use planning database (period 2010 - 2020) for Vung Tau city with 6 data layers, including land use planning data layer (15.060 records), project layer (163 records), adjustment layer for land use planning (12.002 records), adjustment layer for project (570 records), and 2 attribute data layers of community consultation. The results of this study indicated that the correct model and complete database structure were the basis for successfully building and effectively exploiting the database of land use planning. The designed model could contribute to the planning of land management and improve the efficiency of land use.

Bettagram: Digitalization Of The Marketplace For Android Based Buying Betta Fish

Betta fish is one type of ornamental fish that is easily cultivated in an environment with minimal oxygen conditions and has a variety of unique colors that make Betta fish have a high selling value so that many people do this fish business. In the modern era, a marketplace digitization is needed to accommodate betta fish businessmen in order to facilitate transactions with buyers so that an application called Bettagram is created. The Bettagram application is an application based on the Android operating system built to use the Java programming language. Supported by firebase database-based data storage to store all data entered into this application. In the initial process of making this application, the first stage that is passed is the design of use case diagrams and activity diagrams. Furthermore, designing the application display design and designing the database structure for data storage. After that begins the building stage using the help of the android studio application.

Data communication and storage

Monitoring programs in urban drainage systems generate, potentially, a huge amount of data from sources distributed in the urban environment, working at relatively high sampling rates for extended periods of time. Collecting data using adaptable and reliable communication systems is the first challenge. Then structuring the collected data is a first requisite for effectively managing the quality and accessibility of the data. In adjacent fields of research, the topic of managing huge collections of data has resulted in several (open) standards and protocols for database structure, transfer and storage to ensure unambiguous definitions on which parties can build their workflows/software. This chapter describes relevant approaches for urban drainage and stormwater management systems, and appropriate standards along with examples from case studies.

Performance Impact of Optimization Methods on MySQL Document-Based and Relational Databases

Databases are an important part of today’s applications where large amounts of data need to be stored, processed, and accessed quickly. One of the important criteria when choosing to use a database technology is its data processing performance. In this paper, some methods for optimizing the database structure and queries were applied on two popular open-source database management systems: MySQL as a relational DBMS, and document-based MySQL as a non-relational DBMS. The main objective of this paper was to conduct a comparative analysis of the impact that the proposed optimization methods have on each specific DBMS when carrying out CRUD (CREATE, READ, UPDATE, DELETE) requests. To perform the analysis and performance evaluation of CRUD operations for different amounts of data, a case study testing architecture based on Java was developed and used to show how the databases’ proposed optimization methods can influence the performance of the application, and to highlight the differences in response time and complexity. The results obtained show the degree to which the proposed optimization methods contributed to the application’s performance improvement in the case of both databases; based on these, a detailed analysis and several conclusions are presented to support a decision for choosing a specific approach.

Database Management System in Accounting: Assessing the Role of Internet Service Communication of Accounting System Information

Data management is part of information resource management which includes all activities that ensure that company data resources are accurate, up-to-date, and safe from tampering, and are also available to users and the company. This study aims to find out about the role of concept database management in managing large volumes of company data. The result showed that data management activities include data collection, integrity, and testing, storage, maintenance, security, organization, retrieval. Meanwhile, the database structure includes hierarchical database structure, network database structure, and relational database structure.