Bioinformatics Infrastructure in Mozambique
Engineering Excellence & Technical Support
Bioinformatics Infrastructure solutions for Digital & Analytical. High-standard technical execution following OEM protocols and local regulatory frameworks.
National Genomics Data Repository
Deployment of a secure, high-capacity national data repository for storing and managing genomic and other biological datasets. This infrastructure will be crucial for collaborative research, disease surveillance, and biodiversity monitoring, enabling data sharing and reproducibility.
High-Performance Computing Cluster
Establishment of a dedicated High-Performance Computing (HPC) cluster to accelerate complex bioinformatics analyses, including genome assembly, variant calling, and phylogenetic reconstruction. This will significantly reduce processing times, empowering researchers to tackle larger and more intricate biological questions.
Cloud-Enabled Bioinformatics Platform
Implementation of a scalable, cloud-based platform offering access to a suite of pre-installed bioinformatics tools and workflows. This will democratize access to advanced computational resources, reducing reliance on local hardware and facilitating remote collaboration for researchers across Mozambique.
What Is Bioinformatics Infrastructure In Mozambique?
Bioinformatics Infrastructure in Mozambique refers to the integrated set of computational resources, software tools, databases, networks, and specialized expertise that enable the analysis of biological data within the country. This infrastructure is crucial for advancing research, public health, agriculture, and environmental monitoring by facilitating high-throughput data processing, interpretation, and knowledge generation. It encompasses both hardware (e.g., high-performance computing clusters, storage solutions) and software (e.g., bioinformatics pipelines, statistical packages, visualization tools), alongside the human capital and organizational frameworks necessary for their effective deployment and maintenance. The development and accessibility of such infrastructure are pivotal for Mozambique to leverage genomic, transcriptomic, proteomic, and other omics data for addressing national challenges and participating in global scientific endeavors.
| Stakeholder Group | Needs | Typical Use Cases |
|---|---|---|
| Academic Researchers (Universities & Research Institutions) | Access to computational power for complex analyses, data storage, specialized software, collaborative platforms, and training. | Genomic studies of local flora and fauna, infectious disease pathogen sequencing and tracking, agricultural crop improvement, evolutionary biology research. |
| Public Health Agencies (e.g., National Institute of Health, Ministry of Health) | Real-time surveillance of infectious diseases, outbreak investigation, vaccine development support, antimicrobial resistance monitoring, genomic epidemiology. | Sequencing and analysis of HIV, malaria, TB, and emerging pathogens; identifying sources of outbreaks; monitoring drug resistance mutations; developing diagnostic tools. |
| Agricultural Sector (e.g., Agricultural Research Institutes, Seed Companies) | Crop improvement through marker-assisted selection, identification of disease resistance genes, livestock genomics, understanding soil microbiome. | Developing climate-resilient crops, improving livestock breeds, optimizing fertilizer use, identifying pests and diseases. |
| Environmental Agencies | Biodiversity assessment, ecological monitoring, understanding impacts of environmental change, environmental forensics. | DNA barcoding for species identification, metagenomic analysis of environmental samples, tracking invasive species, assessing pollution impacts. |
| Biotechnology Companies | Drug discovery and development, diagnostics development, industrial biotechnology. | Genomic screening for novel drug targets, developing rapid diagnostic tests, optimizing microbial fermentation processes. |
| Students and Educators | Learning resources, hands-on training, access to simplified tools and datasets. | Educational projects, thesis research, skill development for future bioinformatics professionals. |
Components of Bioinformatics Infrastructure in Mozambique
- High-Performance Computing (HPC) resources: Dedicated servers, clusters, or cloud-based computing platforms for intensive data analysis.
- Data Storage Solutions: Secure and scalable repositories for managing large biological datasets.
- Bioinformatics Software Suites and Tools: Pre-installed and readily accessible software for sequence alignment, variant calling, phylogenetic analysis, functional annotation, etc.
- Biological Databases: Local or remote access to curated databases containing genomic, proteomic, and other biological information.
- Network Connectivity: Reliable and high-speed internet access for data transfer and remote access to resources.
- Specialized Expertise and Training: Skilled bioinformaticians, data scientists, and computational biologists, along with ongoing training programs.
- Data Management and Governance Policies: Frameworks for ensuring data integrity, security, privacy, and responsible sharing.
Who Needs Bioinformatics Infrastructure In Mozambique?
Establishing robust bioinformatics infrastructure in Mozambique is crucial for advancing scientific research, public health, and economic development. This infrastructure will empower various stakeholders to leverage genomic and molecular data for a range of critical applications, from disease surveillance to agricultural innovation. Identifying the key beneficiaries and their specific needs is essential for designing effective and sustainable solutions.
| Customer Group | Key Departments/Units | Specific Needs & Applications | Impact Areas |
|---|---|---|---|
| Academic and Research Institutions | University Departments (Biology, Medicine, Agriculture, Computer Science), Research Centers, Institutes | Genomic sequencing data analysis, transcriptomics, proteomics, comparative genomics, evolutionary studies, drug discovery, development of new diagnostic tools, high-throughput data processing, access to public databases. | Scientific advancement, training future researchers, innovation, knowledge generation. |
| Public Health Sector | National Directorate of Public Health, National Institute of Health, Provincial Health Directorates, Disease Surveillance Units, Diagnostic Laboratories, Veterinary Services | Pathogen sequencing for outbreak investigation (e.g., COVID-19, Malaria, HIV), antimicrobial resistance monitoring, vaccine efficacy studies, epidemiological modeling, personalized treatment strategies, genomic surveillance of zoonotic diseases. | Disease prevention and control, improved public health outcomes, rapid response to epidemics, enhanced healthcare system efficiency. |
| Agricultural Sector | Ministry of Agriculture and Rural Development, National Agricultural Research Institutes, Crop and Livestock Research Centers, Extension Services | Crop breeding for drought resistance, pest resistance, and improved yield; livestock genomics for disease resistance and productivity; soil microbiome analysis for sustainable farming; food safety and traceability. | Food security, improved farmer livelihoods, economic growth in agriculture, sustainable resource management. |
| Government Agencies and Policy Makers | Ministry of Science and Technology, Ministry of Health, Ministry of Agriculture, Ministry of Environment, National Planning Commission | Data-driven policy development for health, agriculture, and environmental protection; risk assessment for emerging threats; national research agenda setting; evidence for investment in research and development. | Informed policy decisions, strategic national development, effective resource allocation, national competitiveness. |
| Private Sector and Industry | Pharmaceutical companies, diagnostic companies, biotechnology startups, agricultural input suppliers | Drug discovery and development, development of novel diagnostics, optimization of agricultural products, market analysis based on genetic data, quality control. | Economic diversification, job creation, technological innovation, export potential, local manufacturing capacity. |
| NGOs and International Organizations | WHO, UNICEF, UNAIDS, Médecins Sans Frontières, local health and development NGOs | Health program monitoring and evaluation, disease burden estimation, impact assessment of interventions, data analysis for grant proposals, community health initiatives. | Effective program delivery, improved health and development outcomes, evidence-based advocacy, international collaboration. |
Target Customers and Departments for Bioinformatics Infrastructure in Mozambique
- {"title":"Academic and Research Institutions","description":"These institutions are at the forefront of scientific discovery and require access to cutting-edge bioinformatics tools and high-performance computing for complex data analysis."}
- {"title":"Public Health Sector","description":"Crucial for disease surveillance, outbreak investigation, vaccine development, and personalized medicine initiatives. Infrastructure will enable rapid identification and tracking of pathogens."}
- {"title":"Agricultural Sector","description":"Supports crop improvement, livestock health, food security, and sustainable agricultural practices through genomic analysis and breeding programs."}
- {"title":"Government Agencies and Policy Makers","description":"Provides evidence-based data for informed decision-making in areas such as public health policy, environmental management, and national research strategies."}
- {"title":"Private Sector and Industry","description":"Enables innovation in areas like pharmaceuticals, diagnostics, and biotechnology, fostering economic growth and job creation."}
- {"title":"Non-Governmental Organizations (NGOs) and International Organizations","description":"Supports their work in health, development, and conservation by providing data analysis capabilities for project implementation and impact assessment."}
Bioinformatics Infrastructure Process In Mozambique
The bioinformatics infrastructure process in Mozambique is a structured workflow designed to address the needs of researchers and institutions requiring computational biology support. It typically begins with an inquiry, where a researcher or team identifies a need for bioinformatics services, such as data analysis, software installation, or computational resource access. This inquiry is then formally submitted through designated channels, often to a central bioinformatics unit or coordinating body. Upon receipt, an assessment phase takes place. This involves understanding the specific project requirements, the type of data involved, the desired outcomes, and the available resources. The team might engage in detailed discussions, review project proposals, and determine the feasibility of the request within the existing infrastructure. Following the assessment, a proposal and planning stage is initiated. This includes outlining the methodology, the bioinformatics tools and pipelines to be used, the timeline for execution, and any required data management strategies. A formal proposal, detailing the scope of work and expected deliverables, is often generated. Once the proposal is approved and resources are allocated, the execution phase begins. This is where the actual bioinformatics work is performed, which could involve data processing, alignment, variant calling, statistical analysis, visualization, or the development of custom scripts. Throughout execution, monitoring and communication are crucial, with regular updates provided to the inquirer. Upon completion of the analysis, a reporting and delivery phase ensures that the findings are communicated effectively. This typically involves generating comprehensive reports, visualizations, and the raw or processed data. Finally, a follow-up and feedback stage is often included to assess the satisfaction with the delivered services and to identify areas for improvement in future processes.
| Stage | Description | Key Activities | Outputs |
|---|---|---|---|
| Inquiry | Initial identification of a bioinformatics need by a researcher or institution. | Contacting the bioinformatics unit/coordinator, submitting a request form or proposal outline. | Formal request submitted. |
| Assessment | Understanding and evaluating the scope and requirements of the bioinformatics request. | Consultations with the inquirer, review of project goals, data types, and expected outcomes, feasibility analysis. | Understanding of project requirements, initial resource estimation. |
| Proposal and Planning | Developing a detailed plan and formalizing the agreement for the bioinformatics service. | Defining methodologies, selecting tools/pipelines, estimating timelines, allocating resources, developing data management plans, generating a formal proposal. | Approved project proposal, defined project plan. |
| Execution | Performing the actual bioinformatics analysis and computational tasks. | Data preprocessing, running analysis pipelines, scripting, model building, quality control checks. | Processed data, analytical results. |
| Monitoring and Communication | Tracking the progress of the execution and keeping the inquirer informed. | Regular progress updates, milestone reviews, addressing emergent issues, collaborative problem-solving. | Informed inquirer, timely issue resolution. |
| Reporting and Delivery | Presenting the results of the bioinformatics analysis to the inquirer. | Generating reports, creating visualizations, preparing data summaries, delivering raw/processed data. | Final project report, visualizations, delivered data. |
| Follow-up and Feedback | Ensuring client satisfaction and gathering input for process improvement. | Post-project discussion, feedback collection, assessing impact, identifying lessons learned. | Client satisfaction confirmed, input for process enhancement. |
Bioinformatics Infrastructure Process Workflow in Mozambique
- Inquiry
- Assessment
- Proposal and Planning
- Execution
- Monitoring and Communication
- Reporting and Delivery
- Follow-up and Feedback
Bioinformatics Infrastructure Cost In Mozambique
Assessing the bioinformatics infrastructure costs in Mozambique requires a nuanced understanding of local economic conditions, import duties, and the availability of specialized hardware and software. Unlike developed nations where dedicated research budgets might cover proprietary solutions, Mozambique often relies on a combination of government initiatives, international grants, and a growing reliance on open-source tools. The cost breakdown typically involves hardware (servers, workstations, storage), software (licenses, cloud subscriptions), networking, and crucially, skilled personnel for maintenance and operation. Pricing factors are heavily influenced by import tariffs on electronics, the US dollar exchange rate, and the limited local market for highly specialized bioinformatics equipment, which often necessitates international procurement. Expect significant variability based on the scale of operation, from a small departmental setup to a national genomics center. Local currency costs are thus a reflection of international market prices translated through the Mozambican Metical (MZN), with added layers of import-related expenses.
| Component/Service | Estimated Cost Range (MZN) | Notes & Pricing Factors |
|---|---|---|
| Basic Server (Departmental) | 150,000 - 500,000 | Depends on CPU cores, RAM, storage capacity. International pricing + import duties. Often procured through grants. |
| High-Performance Compute (HPC) Node (per node) | 300,000 - 1,000,000+ | Significant investment. Requires specialized components. Typically for national/regional centers, often funded by grants or government initiatives. |
| High-Capacity Storage (e.g., 50TB NAS) | 200,000 - 750,000+ | Scalable; cost increases with capacity and speed (SSD vs. HDD). Import costs are a major factor. |
| Powerful Workstation (Bioinformatics-grade) | 100,000 - 300,000 | Good CPU, ample RAM, dedicated GPU for visualization. Varies with brand and specifications. |
| Networking Switch (Managed, Gigabit) | 30,000 - 150,000 | Depends on port count and features. Essential for data transfer efficiency. |
| Open-Source Software Support (Annual) | 0 - 50,000+ | Primarily internal IT support. Paid support contracts can be expensive but offer guaranteed response times. |
| Commercial Software License (Annual - e.g., specialized analysis software) | 50,000 - 500,000+ | Highly variable. Often depends on the vendor, number of users, and specific modules. Significant exchange rate impact. |
| Cloud Computing (e.g., AWS/Azure/Google Cloud - monthly usage) | 10,000 - 200,000+ | Pay-as-you-go. Heavily influenced by compute instance types, storage, and data transfer. A cost-effective alternative for fluctuating needs. |
| Bioinformatician Salary (Junior/Mid-level - monthly) | 40,000 - 100,000+ | Reflects local market rates and demand for specialized skills. Often supplemented by international funding for research projects. |
| Generator/UPS (Reliable Power) | 50,000 - 250,000+ | Essential given potential power instability. Capacity and reliability dictate price. |
Key Bioinformatics Infrastructure Components and Cost Considerations in Mozambique:
- Servers and Compute Clusters: Essential for processing large genomic datasets. Costs can range from basic departmental servers to powerful HPC (High-Performance Computing) clusters for national-level research.
- Storage Solutions: High-capacity storage is critical for raw sequencing data, processed results, and databases. This includes NAS (Network Attached Storage) and SAN (Storage Area Network) solutions.
- Workstations and Laptops: For data analysis, visualization, and software development by individual researchers and bioinformaticians.
- Networking Equipment: Robust and high-speed networking is vital for data transfer between storage, compute, and users.
- Software Licenses: While many bioinformatics tools are open-source, some specialized commercial software (e.g., advanced visualization tools, proprietary analysis pipelines) may require licenses.
- Cloud Computing Services: Increasingly adopted for flexibility and scalability, especially for organizations that cannot afford large upfront hardware investments. Costs are subscription-based and vary by provider and usage.
- Power and Cooling Infrastructure: Reliable electricity and adequate cooling systems are paramount for server uptime and longevity.
- Skilled Personnel: The cost of hiring and retaining qualified bioinformaticians, IT administrators, and support staff is a significant ongoing expense.
- Maintenance and Support Contracts: For hardware and software, ensuring continuous operation and access to technical assistance.
- Training and Capacity Building: Investing in training for staff to effectively utilize and maintain the infrastructure.
Affordable Bioinformatics Infrastructure Options
Acquiring and maintaining robust bioinformatics infrastructure can be a significant investment for research institutions, startups, and even individual researchers. Fortunately, a range of affordable options exist, emphasizing value bundles and strategic cost-saving measures. Understanding these options allows for the efficient allocation of resources without compromising computational power or data accessibility.
| Infrastructure Component | Cost-Saving Strategy | Value Proposition |
|---|---|---|
| Compute Power (CPU/GPU) | Cloud 'Spot Instances' or 'Preemptible VMs' | Significant cost reduction for non-critical or fault-tolerant workloads. |
| Compute Power (CPU/GPU) | On-premises HPC clusters with shared access | Predictable operational costs, potential for long-term cost efficiency with high utilization. |
| Storage | Object storage with intelligent tiering (e.g., AWS S3 Intelligent-Tiering) | Automated cost optimization by moving data between access tiers. |
| Storage | Network Attached Storage (NAS) or Storage Area Network (SAN) with pooled resources | Centralized management, economies of scale, and shared acquisition costs. |
| Software Licensing | Open-source alternatives and community-supported tools | Eliminates direct software acquisition costs and reduces vendor lock-in. |
| Software Licensing | Site licenses or academic volume discounts | Lower per-user or per-institution costs for commercial software. |
| Networking | Optimized bandwidth allocation and traffic shaping | Ensures efficient use of existing network resources, avoiding costly upgrades. |
| Data Transfer | Leveraging cloud provider's free tier egress or optimized data pipelines | Minimizes costs associated with moving large datasets in and out of cloud environments. |
| System Administration | Managed cloud services or outsourcing | Reduces the need for in-house IT staff and specialized skill sets. |
Key Value Bundles and Cost-Saving Strategies
- Cloud Computing Services: Major providers like AWS, Google Cloud, and Azure offer scalable infrastructure, pay-as-you-go models, and often have specific programs for academic research, providing significant discounts.
- Open-Source Software and Tools: Leveraging freely available bioinformatics software (e.g., Bioconductor, Galaxy, Nextflow) drastically reduces licensing costs.
- Shared or Pooled Resources: Collaborating with other institutions or departments to share hardware (e.g., high-performance computing clusters) or software licenses can distribute costs.
- Managed Services: Outsourcing certain infrastructure management tasks (e.g., data storage, security, system administration) to specialized providers can be more cost-effective than in-house expertise.
- Containerization (Docker/Singularity): Facilitates reproducible research and simplifies deployment of complex software environments, reducing setup time and potential conflicts on shared infrastructure.
- Virtualization (VMs): Allows for efficient utilization of hardware by running multiple operating systems and applications on a single physical server.
- Optimized Storage Solutions: Employing tiered storage strategies (e.g., hot for active data, cold for archival) balances accessibility and cost.
- Leveraging Academic/Research Discounts: Actively seeking out and applying for specific discounts offered to educational and research institutions by software and hardware vendors.
- Community Support and Collaboration: Engaging with online bioinformatics communities can provide free technical support and advice, reducing the need for paid support contracts.
- Strategic Hardware Purchasing: Investing in refurbished hardware or timing purchases with vendor upgrade cycles can offer substantial savings.
Verified Providers In Mozambique
Ensuring access to quality healthcare is paramount, and in Mozambique, identifying verified providers is crucial for patient safety and effective treatment. Franance Health stands out as a leader in this regard, meticulously vetting its network of healthcare professionals and facilities. This rigorous credentialing process is not merely a formality; it's a cornerstone of their commitment to providing superior healthcare services. By adhering to stringent standards and conducting thorough background checks, Franance Health ensures that every provider within their network possesses the necessary qualifications, expertise, and ethical standing to deliver exceptional patient care. Choosing Franance Health means choosing a partner dedicated to your well-being, backed by a transparent and reliable system of verified healthcare professionals.
| Credentialing Aspect | Franance Health Standard | Benefit to Patient |
|---|---|---|
| Medical Licensing & Certifications | Verification of current and valid licenses and specialized certifications | Ensures providers are legally qualified and possess the required expertise. |
| Educational Background Review | Thorough examination of academic qualifications from accredited institutions | Guarantees a strong foundation in medical knowledge and practice. |
| Clinical Experience Assessment | Evaluation of practical experience and areas of specialization | Confirms hands-on skills and suitability for specific patient needs. |
| Professional References & Peer Review | Collection of feedback from professional colleagues and supervisors | Provides insights into a provider's performance and ethical conduct. |
| Background Checks | Comprehensive checks for any disciplinary actions or legal issues | Safeguards patients by ensuring providers have a clean professional history. |
| Continuing Medical Education (CME) | Verification of ongoing commitment to professional development | Ensures providers stay updated with the latest medical advancements and techniques. |
Why Franance Health Credentials Represent the Best Choice:
- Rigorous Vetting Process: Franance Health employs a multi-faceted approach to credentialing, going beyond basic requirements to ensure providers meet the highest standards of competence and ethics.
- Experienced and Qualified Professionals: All providers within the Franance Health network are thoroughly assessed for their educational background, clinical experience, and specialized skills.
- Commitment to Patient Safety: The credentialing process prioritizes patient well-being by verifying licenses, certifications, and a clean disciplinary record.
- Reputation and Trustworthiness: Franance Health partners with providers who have a proven track record of delivering excellent care and maintaining patient trust.
- Access to a Comprehensive Network: By choosing Franance Health, patients gain access to a wide array of verified specialists and facilities across Mozambique.
- Transparent Verification: Franance Health maintains transparency in its credentialing process, offering peace of mind to patients seeking reliable healthcare.
Scope Of Work For Bioinformatics Infrastructure
This Scope of Work (SOW) outlines the technical deliverables and standard specifications for the establishment and maintenance of a robust bioinformatics infrastructure. The goal is to provide a scalable, secure, and efficient environment to support research, data analysis, and collaboration in the field of genomics and related life sciences.
| Deliverable | Description | Technical Specifications/Standards | Acceptance Criteria |
|---|---|---|---|
| HPC Cluster | Provision of a compute cluster optimized for bioinformatics workloads. | Minimum 100 compute nodes, each with >= 64 CPU cores, >= 256GB RAM. Interconnect: High-speed (e.g., InfiniBand FDR/HDR). Storage: Parallel file system (e.g., Lustre, BeeGFS) with >1PB capacity, high IOPS. Scheduler: Slurm or equivalent. | Cluster operational and benchmarks demonstrate expected performance for typical bioinformatics jobs (e.g., genome assembly, variant calling). |
| Data Storage Solution | Secure, centralized, and scalable storage for genomic data. | Tiered storage: Fast, high-performance storage for active data (e.g., NVMe SSDs), and large-capacity, cost-effective storage for archival (e.g., HDD, tape). Capacity: Minimum 5PB expandable to 20PB. Protocols: NFS, SMB, S3-compatible API. Data Lifecycle Management policies. | Data accessible via defined protocols. Backup and recovery procedures tested and validated. Data retention policies implemented. |
| Bioinformatics Software Suite | Installation and configuration of commonly used bioinformatics tools. | Operating System: Linux (e.g., CentOS Stream, Ubuntu LTS). Software: Nextflow, Singularity/Apptainer, Samtools, BWA, GATK, VEP, QIIME2, R/Bioconductor, Python (Biopython, Pandas, NumPy). Containerization: Docker/Singularity images for reproducible pipelines. | All specified software installed and functional. Pipelines demonstrable using reference datasets. Version control implemented for software configurations. |
| Network Infrastructure | High-speed and reliable network connectivity within the infrastructure. | 10/40/100 Gbps Ethernet for compute and storage connectivity. Secure access controls and firewall rules. Remote access via VPN. | Network latency within specified thresholds. Secure remote access established and tested. |
| Security and Access Control | Implementation of robust security measures and user access management. | Role-based access control (RBAC). Data encryption at rest and in transit. Regular security audits and vulnerability assessments. Intrusion detection/prevention systems. Secure user authentication (e.g., LDAP, Active Directory integration). | Access logs audited. Security policies documented and enforced. Penetration testing passed. |
| Backup and Disaster Recovery | Comprehensive backup and disaster recovery strategy. | Regular automated backups of all critical data and configurations. Offsite backup location. Documented disaster recovery plan with defined RPO/RTO. Periodic DR drills. | Backup and restore operations successfully tested. DR plan validated through drills. |
| Monitoring and Management Tools | Tools for monitoring system health, performance, and resource utilization. | Monitoring: Prometheus/Grafana, Nagios, Zabbix. Resource Management: SLURM accounting, user quotas. Logging: Centralized logging system (e.g., ELK stack). | All systems monitored. Alerting mechanisms configured. Performance metrics available via dashboards. |
| Documentation and Training | Comprehensive documentation and user training. | System architecture diagrams, installation guides, user manuals, troubleshooting guides. Training sessions for researchers on system usage and best practices. | Documentation is complete, accurate, and accessible. Training sessions delivered and attendance recorded. |
Key Objectives
- Establish a high-performance computing (HPC) cluster for large-scale genomic data processing.
- Implement a secure and scalable data storage solution for raw and analyzed genomic datasets.
- Deploy and configure essential bioinformatics software and tools for common research workflows.
- Ensure robust data security, backup, and disaster recovery mechanisms.
- Provide user-friendly access and support for researchers.
- Establish a framework for ongoing maintenance, updates, and capacity planning.
Service Level Agreement For Bioinformatics Infrastructure
This Service Level Agreement (SLA) outlines the guaranteed response times and uptime for the provided Bioinformatics Infrastructure. It defines the responsibilities of the service provider and the client, and establishes metrics for service availability and performance.
| Service Component | Uptime Guarantee | Response Time (Standard Support) | Response Time (Critical Incident) |
|---|---|---|---|
| Core Compute Clusters (e.g., HPC) | 99.8% (excluding scheduled maintenance) | Within 4 business hours | Within 1 business hour (acknowledgement) |
| Data Storage (e.g., NAS, SAN) | 99.9% (excluding scheduled maintenance) | Within 6 business hours | Within 2 business hours (acknowledgement) |
| Bioinformatics Software Suite (e.g., Galaxy, Snakemake instances) | 99.5% (excluding scheduled maintenance) | Within 8 business hours | Within 4 business hours (acknowledgement) |
| Database Services (e.g., LIMS, Reference Databases) | 99.7% (excluding scheduled maintenance) | Within 4 business hours | Within 1 business hour (acknowledgement) |
| Network Connectivity to Infrastructure | 99.95% (excluding scheduled maintenance) | Within 2 business hours | Within 30 minutes (acknowledgement) |
Key Definitions
- Uptime: The percentage of time the Bioinformatics Infrastructure is available and operational.
- Response Time: The time taken for the system to acknowledge and begin processing a request.
- Downtime: Any period when the Bioinformatics Infrastructure is unavailable or not functioning as expected.
- Maintenance Window: Pre-scheduled periods for planned maintenance, upgrades, or repairs, during which service may be interrupted. These will be communicated in advance.
- Critical Incident: An event that renders a core functionality of the Bioinformatics Infrastructure completely unusable, impacting multiple users or critical research workflows.
- Major Incident: An event that significantly degrades the performance or availability of a core functionality, impacting a substantial portion of users or research workflows.
- Minor Incident: An event that causes localized or minor degradation of performance or availability, impacting a limited number of users or non-critical workflows.
Frequently Asked Questions
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