package) 20 1. Multiple 2. Scalable RDBMS 1. Huge data 1. Real-time 1. Login 1. Methods to -- Comparative centralized data for heterogeneous storage interactive security: improve data quality Analysis for sources biological data parallel bulk username and 2. Data clustering, 2. Proteins and 2. Real-time rapid loading password classification, and their structural and parallel bulk capability 2. Creation of reduction Genomes features, core loading 2. Interactive user account to 3. Integration of genomic data, 3. Oracle RDBMS, Web UI, submit and new data/content new types of SQLite files, flat backend access dataset into the system’s omics data such text files, Lucy (a to system via data store and data as version of Lucene) batch job web interface annotation transcriptomics, for keyword computation 3. Single methylomics, and searches, BLAST submission capability proteomics databases, from the UI. (SSO) describing gene USEARCH 3. Download expression databases of assembled 3. Front real-time 4. Linux cluster, and annotated web UI Oracle RDBMS datasets for interactive; server, large offline analysis backend data memory machines, 4. Ability to loading standard Linux query and processing that interactive hosts browse data keeps up with 5. Sequencing and via interactive exponential comparative web UI growth of analysis techniques 5. Visualize sequence data for highly complex data structure due to the rapid data at different drop in cost of 6. Descriptive levels of sequencing statistics resolution; technology ability to view 4. abstract Heterogeneous, complex, of highly structural, and similar data hierarchical
package) 20 Comparative Analysis for and Genomes 1. Multiple centralized data sources 2. Proteins and their structural features, core genomic data, new types of omics data such as transcriptomics, methylomics, and proteomics describing gene expression 3. Front real-time web UI interactive; backend data loading processing that keeps up with exponential growth of sequence data due to the rapid drop in cost of sequencing technology 4. Heterogeneous, complex, structural, and hierarchical 2. Scalable RDBMS for heterogeneous biological data 2. Real-time rapid and parallel bulk loading 3. Oracle RDBMS, SQLite files, flat text files, Lucy (a version of Lucene) for keyword searches, BLAST databases, USEARCH databases 4. Linux cluster, Oracle RDBMS server, large memory machines, standard Linux interactive hosts 5. Sequencing and comparative analysis techniques for highly complex data 6. Descriptive statistics 1. Huge data storage 1. Real-time interactive parallel bulk loading capability 2. Interactive Web UI, backend batch job computation submission from the UI. 3. Download of assembled and annotated datasets for offline analysis 4. Ability to query and browse data via interactive web UI 5. Visualize data structure at different levels of resolution; ability to view abstract of highly similar data 1. Login security: username and password 2. Creation of user account to submit and access dataset to system via web interface 3. Single capability (SSO) 1. Methods to improve data quality 2. Data clustering, classification, reduction 3. Integration of new data/content into the system’s data store and data annotation --