Reframing bioinformatics capacity development in Africa: from training supply to research-driven demand

Abstract

Bioinformatics has become central to modern genomics and data-intensive life science research, yet capacity development across Africa remains uneven. This review examines the evolution of bioinformatics capacity on the continent, evaluating historical investments in training, infrastructure, and collaborative research initiatives. Using narrative synthesis, we assess major continental programs including H3Africa and post-H3ABioNet initiatives. Evidence reviewed suggests that bioinformatics capacity development is most sustainable when skills development and research facilities investments are embedded within funded, data-generating research programs. Regional case studies show that research-led environments promote workforce retention and scientific productivity. Persistent challenges including infrastructure limitations and uneven investment continue to affect analytical capacity and competitiveness. The review proposes a demand-driven framework in which sustained research funding, data production, and embedded training mutually reinforce long-term bioinformatics development. Such an approach may better support locally led genomic research and strengthen Africa’s participation in global data science and precision health initiatives.

Introduction

Introduction and background

Bioinformatics integrates biology, computing, and data analysis to support modern life science research (Akintola et al. 2024). Since the sequencing of the first genomes in the 1990s, advances in high-throughput technologies have expanded its role across nearly all areas of the life sciences (Bishop et al. 2014). This growth has increased demand for skilled bioinformaticians, which remains unevenly met across Africa.

The imperative for Africa

Africa’s dual burden of infectious and non-communicable diseases underscores the need for bioinformatics-supported genomic research (Shaffer et al. 2019). Bioinformatics supports analysis of pathogen evolution, drug resistance, and host–pathogen interactions, enabling improved treatments and surveillance strategies (Shaffer et al. 2019; Mboowa et al. 2024). Africa’s genetic diversity provides insights into human evolution and disease susceptibility, reinforcing the need for locally relevant genomic research (Mboowa et al. 2024). These drivers are summarized in Fig. 1.

Fig. 1.

Key drivers necessitating bioinformatics development in Africa, including disease burden, genetic diversity, and the need for locally relevant genomic research and healthcare solutions

Historical capacity gaps

Despite this potential, Africa has historically been underrepresented in genomics research. Only a small proportion of genome-wide association studies have included African populations (Bishop et al. 2014; Matovu et al. 2014). Limited availability of experienced bioinformaticians and trained faculty has further constrained research participation and training capacity across many institutions (Bishop et al. 2014; Chimusa et al. 2015; Mulder et al. 2016a; Akintola et al. 2024). In response to historical underrepresentation in genomics, several initiatives have strengthened bioinformatics capacity across Africa. The Human Heredity and Health in Africa (H3Africa) initiative was initiated in 2010 and formally launched in 2012 to enable African-led genomic research (Ramsay 2015; Bendou et al. 2016). Its bioinformatics network, H3ABioNet, operated from 2012 to 2023, supporting training, infrastructure, and collaboration (Adoga et al. 2014; Mulder et al. 2016a). H3ABioNet trained over 4,400 participants and deployed computational infrastructure across 15 countries (Mulder et al. 2016a; Aron et al. 2021b).

Additional programs, including EANBiT, the African BioGenome Project, and university-based initiatives, have expanded training and collaboration opportunities (Mboowa et al. 2024; Akintola et al. 2024). International partnerships continue to support knowledge transfer (Akintola et al. 2024; Mulder et al. 2017). Despite these investments, progress has been uneven (Karikari 2015; Hamdi et al. 2021). This review examines whether training deficits alone explain capacity gaps, or whether research funding and data generation play a more decisive role.

Methodology

This review employed a narrative synthesis approach to examine bioinformatics capacity development in Africa. Literature was identified through searches of PubMed, Scopus, Web of Science, Google Scholar, and relevant institutional repositories for publications from 2010 to 2026. Search terms combined “bioinformatics,” “capacity building,” “training,” “infrastructure,” and “Africa.” Inclusion criteria required focus on African bioinformatics capacity, training programs, infrastructure, funding, or governance. Peer-reviewed articles, program evaluations, and policy documents were included; opinion pieces and non-African studies were excluded. Data were extracted on workforce, infrastructure, funding, and governance. Given the heterogeneity of studies, narrative synthesis was used to identify themes including demand-driven capacity, sustainability and equity.

Current landscape and major initiatives

The current bioinformatics landscape in Africa reflects both progress and persistent structural gaps. Expertise remains unevenly distributed across the continent, and demand for bioinformatics skills continues to exceed supply (Mulder et al. 2017; Karikari 2015). However, evidence suggests that limited research funding and data generation (Mulder et al. 2016a; Wonkam 2021), rather than training deficits alone, are key constraints, as trained bioinformaticians often face underemployment in the absence of funded research positions.

H3Africa and H3ABioNet

A major turning point in African bioinformatics was the establishment of the Human Heredity and Health in Africa (H3Africa) initiative and its bioinformatics network, H3ABioNet, which operated from 2012 to 2023 (Mohamed et al. 2021; Adoga et al. 2014). H3ABioNet became one of the continent’s largest bioinformatics capacity investments, supporting research grants, training, and computational infrastructure across multiple African institutions (Karikari 2015; Mulder et al. 2016a).

At its launch, the network deployed 15 servers across African nodes, providing 512 cores, 2,384 GB RAM, and 120 terabytes storage. This infrastructure was supported by 40 + funded staff and 80 + additional contributors from participating institutions (Mulder et al. 2016a). Over its 11-year funding period, this infrastructure expanded substantially, ultimately reaching 17 computing facilities with 3,432 cores and 1.2 petabytes (PB) of storage, serving 28 nodes across 17 countries (16 in Africa) (H3ABioNet 2025)

The network developed continent-wide training and reproducible workflows suited to heterogeneous environments (Gurwitz et al. 2017; Ahmed et al. 2019; Baichoo et al. 2018). By May 2021, H3ABioNet had trained 4,466 unique participants, with approximately 70% (3,024 individuals) completing its Introduction to Bioinformatics (IBT) course. Despite COVID-19 disruptions, the network trained over 1,200 people in 2020 through adapted mixed-model delivery (Aron et al. 2021b).

Although no longer active, its legacy persists through trained personnel and institutional infrastructure. The end of H3ABioNet has also prompted reflection on the sustainability of project-based capacity building.

Supporting organizations and networks

Several organizations have supported continental bioinformatics development. The African Society for Bioinformatics and Computational Biology (ASBCB) has facilitated collaboration, training, and professional networking since its establishment in 2004 (Mohamed et al. 2021). The African Society of Human Genetics has similarly contributed through training programs and partnerships aimed at strengthening research infrastructure (Karikari 2015).

Regional leadership

Regional leadership has emerged from countries with sustained investment in research infrastructure. South Africa has played a central role since the establishment of the South African National Bioinformatics Institute, supported by government funding and integration into university systems (Mwita et al. 2023; Mohamed et al. 2021; Mulder et al. 2016b). In West Africa, Nigeria and Ghana advanced early through academic programs, workshops, and the establishment of national networks such as the Nigerian Bioinformatics and Genomics Network (Tibiri et al. 2024; Fatumo et al. 2014).

Post-H3ABioNet initiatives

The completion of H3ABioNet funding marked a transition toward new institutional models for capacity development.

African centers of excellence in bioinformatics (ACEB)

The ACEB program, supported by the U.S. National Institute of Allergy and Infectious Diseases, established regional centers in Mali, Ghana, and Zambia to provide training, infrastructure, and data analysis support for infectious disease research (Giovanni et al. 2022). At ACE-Mali, the program graduated 47 MSc students and produced over 25 publications (Cisse et al. 2025), despite operating in a challenging environment characterized by unreliable power, and limited internet connectivity (Proffitt 2021). In contrast, ACE-Uganda expanded more rapidly, adding 56 new computing nodes and increasing capacity five-fold by 2025, through partnerships (ACE Uganda 2025; U.S. Embassy Uganda 2025). This variability in outcomes highlights the importance of linking bioinformatics centers with active research programs and adapting infrastructure investments to local contexts (Giovanni et al. 2022; Proffitt 2021).

Data Science for health discovery and innovation in Africa (DS-I Africa)

Launched in 2021 with support from the NIH Common Fund, DS-I Africa represents a shift toward integrating data science training with large-scale research programs (Mistry et al. 2023). The initiative supports collaborative research hubs focused on health challenges such as antimicrobial resistance, environmental health, and neurodevelopmental disorders. Embedded bioinformatics and data science cores create demand for skilled researchers and support long-term capacity development (Agamah et al. 2025).

African bioinformatics institute (ABI)

The African Bioinformatics Institute (ABI), established in 2022 with support from the Wellcome Trust and the Chan Zuckerberg Initiative, represents a move toward permanent institutional infrastructure for bioinformatics on the continent (Mulder 2025). Although its permanent hub is not yet selected and currently interim at the University of Cape Town, the institute aims to coordinate research, training, and data infrastructure across Africa through planned regional nodes. Its focus includes developing federated data environments, strengthening governance frameworks, and supporting large-scale genomic and public health data initiatives (Mulder 2025).

Africa CDC Africa pathogen genomics initiative (Africa PGI)

Launched by the Africa Centres for Disease Control and Prevention, the Africa Pathogen Genomics Initiative (Africa PGI) represents a major public-health focused investment in bioinformatics capacity. The initiative aims to build a continent-wide functional network of pathogen genomics and bioinformatics, including next-generation sequencing capacity in 20 national public health institutes and regional laboratory hubs for training and technical support (Africa 2022).

Africa PGI integrates bioinformatics training with public health surveillance through fellowships with dry-lab tracks in analytics and reporting. This model embeds bioinformatics capacity within national health systems rather than research projects alone, creating potential for sustained operational funding and career pathways aligned with disease control priorities.

The initiative’s emphasis on standardized protocols, secure data exchange, and routine surveillance-linked sequencing represents a distinct infrastructure class with implications for workforce development, data governance, and long-term sustainability. The historical development of these initiatives is illustrated chronologically in Fig. 2.

Fig. 2.

Evolution of African bioinformatics capacity development (1996–2025), illustrating the transition from early institutional foundations to large-scale, research-embedded and demand-driven initiatives

The historical development and scope of these initiatives are summarized in Table 1, which provides a comparative overview of their focus areas, key achievements, and funding status (compiled from Mulder et al. 2016a; Giovanni et al. 2022; Agamah et al. 2025; Africa 2022).

Table 1.

Major African bioinformatics initiatives (1996–2025). Summary of key programs, their focus areas, achievements, and funding status

Initiative	Period	Focus	Key achievements	Funding status
SANBI (South Africa)	1996–present	National bioinformatics institute	Pioneer in African bioinformatics; trained hundreds of postgraduate students	Government core funding + grants
H3ABioNet	2012–2023	Pan-African bioinformatics network	4,466 trainees; 17 computing facilities (3,432 cores, 1.2 petabytes storage); 40 + funded staff; 28 nodes in 17 countries (16 in Africa)	NIH/Wellcome Trust (concluded)
ACEB	2019–present	Regional centers of excellence	Centers in Mali, Ghana, Zambia; infrastructure for infectious disease research	NIAID
DS-I Africa	2021–2026	Data science for health research	38 projects; 135 core partners; 7 research hubs; embedded training	NIH Common Fund
ABI	2022–present	Permanent continental institute	Federated data environments; regional nodes (interim at UCT)	Wellcome Trust, CZI
Africa PGI	2022–present	Pathogen genomics surveillance	NGS capacity in 20 national labs; fellowship programs	Africa CDC

Infrastructure and resources

Bioinformatics infrastructure in Africa expanded substantially through targeted capacity-building initiatives, particularly H3ABioNet. H3ABioNet funding supports bioinformatics training and research, as well as the development of computational infrastructure including improved data storage, server capacity and internet bandwidth (Bendou et al. 2016). The network has successfully built capacity through various strategies, including upgrading computing infrastructure in Africa, developing and customizing software tools to facilitate data management and manipulation, and initiating collaborative multidisciplinary research partnerships (Kumuthini et al. 2019; Mulder et al. 2016a ; Adoga et al. 2014; Gurwitz et al. 2017).

Infrastructure development and persistent gaps

The establishment of H3ABioNet came at an opportune time when there had been considerable investment in information communication and technology (ICT) by many African countries, with these countries ensuring that national internet infrastructure is accessible at a subsidized rate to universities and research institutions (Mulder et al. 2016a). However, significant infrastructure challenges persist across the continent. The analysis of omics data remains limited by both human and computational resources, with challenges such as high bandwidth costs and limited international network connectivity continuing to impact bioinformatics platforms (Tibiri et al. 2024; Mwita et al. 2023). Infrastructure without associated research funding risks underuse (Mulder et al. 2016a; Tibiri et al. 2024).

Innovative support systems

H3ABioNet developed innovative support systems to address Africa’s unique infrastructure limitations. Due to the lack of established bioinformatics support resources available to African researchers, H3ABioNet established an online bioinformatics helpdesk that is one of the first public and freely available, generic bioinformatics helpdesks systematically implemented to provide rapid bioinformatics support across Africa and the rest of the world (Kumuthini et al. 2019). The network initially focused on core capacity development through the provision of teaching and training events, coupled with building core computational infrastructure at developing nodes, while addressing low-middle-income country (LMIC) specific challenges such as limited and unstable network connectivity (Choudhury et al. 2021). This helpdesk continues to operate, representing one of H3ABioNet’s sustainable legacies.

Focus on portability and reproducibility

A critical focus has been developing portable and reproducible bioinformatics workflows that can operate on heterogeneous computing environments across Africa. H3ABioNet built capacity for bioinformatics within Africa while developing workflows that should be as portable as possible, given the heterogeneous computing environments of different groups including High Performance Computing (HPC) centers, University and lab clusters, and cloud environments (Baichoo et al. 2018). This approach equips African scientists in resource-scarce settings to analyze genomics data as equal partners rather than data generators, enabling them to compete with better-resourced groups (Baichoo et al. 2018). These workflows remain publicly available and continue to be used by African research groups.

Recent specialized initiatives have further expanded infrastructure development across specific research areas. A Pan-African bioinformatics initiative for malaria vector genomics has established HPC infrastructure to support data storage, processing, and utilization on the continent, addressing the gap where limited computing infrastructure and technical expertise have hindered full utilization of genomic data (Dada et al. 2024). As the network has matured, the emphasis has gradually shifted from basic capacity building to developing sustainable applied informatics solutions to continue supporting the emerging requirements of the H3Africa Consortium (Choudhury et al. 2021). This shift toward applied informatics solutions linked to specific research projects anticipates the design of DS-I Africa and ABI.

Challenges and barriers

Bioinformatics capacity in Africa is shaped by interconnected challenges involving workforce, infrastructure, and research funding. While earlier analyses emphasized shortages of trained personnel and computing infrastructure as the primary constraints (Bishop et al. 2014; Karikari 2015), emerging evidence suggests a more complex structure in which stable research funding and data generation play a central role in shaping bioinformatics expertise (Mulder et al. 2016a; Wonkam 2021).

Supply-side versus demand-driven capacity models

Two conceptual approaches have guided bioinformatics development in Africa. The supply-side model assumes that training more bioinformaticians will lead to increased research productivity and data generation. In contrast, a demand-driven model proposes that bioinformatics expertise develops in response to funded research projects that generate data requiring analysis.

Experience from major initiatives lends weight to the demand-driven view. Programs such as H3Africa, MalariaGEN, and TrypanoGEN demonstrate that when African-led research receives sustained funding and produces substantial datasets, bioinformatics expertise coalesces around those projects, creating durable analytical capacity (Adoga et al. 2014; Mulder et al. 2016a).

Human resource constraints

The shortage of experienced bioinformaticians has long been identified as a barrier to capacity development (Bishop et al. 2014; Karikari 2015; Chimusa et al. 2015). Many institutions lack faculty with expertise to train students, supervise research, and lead genomic projects, limiting participation in high-throughput genomics initiatives.

However, workforce gaps are closely linked to limited research funding and institutional support. Without sustained research funding and permanent positions, trained bioinformaticians struggle to maintain careers or secure employment (Mulder et al. 2016b; Hamdi et al. 2021).

Infrastructure limitations

Infrastructure constraints remain significant across many African countries. Limited access to high-performance computing, unstable internet connectivity, and inconsistent power supply continue to affect the analysis of large-scale genomic data (Karikari 2015; Hamdi et al. 2021). Although investments in computational infrastructure have increased, utilization often depends on the availability of funded research projects.

Infrastructure that is not linked to ongoing data-generating research may remain underused, highlighting the need to align infrastructure development with national and regional research priorities (Mulder et al. 2016a).

Persistent inequalities and institutional gaps

Bioinformatics capacity is concentrated in countries with stronger funding and institutions, particularly South Africa, Nigeria, and Kenya (Mulder et al. 2016b; Wonkam 2021). Elsewhere, access to advanced computing, specialized training, and stable research environments remains limited, reflecting uneven investment and institutional development (Karikari 2015).

These disparities are self-reinforcing: institutions with established infrastructure attract further investment, while weaker foundations struggle to build critical mass or retain trained personnel (Hamdi et al. 2021). The result is a widening gap between research-intensive hubs and institutions dependent on short-term projects (Wonkam 2021). Addressing these inequalities requires targeted support for under-resourced institutions through infrastructure investment and regional collaboration.

Sustainability of capacity-building initiatives

The sustainability of bioinformatics initiatives remains a major concern. Project-based programs often achieve significant short-term success but struggle to maintain momentum once funding cycles end (Adoga et al. 2014; Giovanni et al. 2022). The experience of H3ABioNet illustrates both the achievements of coordinated continental investment and the challenges of transitioning to long-term institutional support (Mulder et al. 2016a). Sustainable capacity requires integration of bioinformatics into university structures, national research priorities, and government funding frameworks (Adoga et al. 2014; Mulder et al. 2016b).

Employment and skills utilization

An emerging challenge is the mismatch between training outputs and employment opportunities (Shaffer et al. 2019). While training programs have produced increasing numbers of bioinformatics graduates, research funding and permanent positions have not expanded at the same pace (Karikari 2015; Hamdi et al. 2021). This can lead to underemployment and limited opportunities to apply newly acquired skills. When training is embedded in funded research environments, it produces both technical competence and employment pathways where trainees engage with real datasets and contribute to scientific outputs (Mulder et al. 2016a; Wonkam 2021).

Data governance implementation capacity

The operational requirements of genomic data governance are often underappreciated in capacity assessments. H3Africa’s data policy requires a nine-month hold, EGA deposition, and independent access decisions each step demanding skills in encryption, metadata curation, identity management, and compliance auditing (H3Africa, 2020). These functions are rarely formally funded as “science” and are often absent from institutional staffing models, creating a gap between policy adoption and implementation capacity. Strengthening bioinformatics therefore requires not only analytical skills but also professional data stewardship roles capable of executing controlled access, maintaining audit trails, and ensuring compliant data release at scale.

Language and structural exclusion

A neglected barrier to equitable bioinformatics capacity in Africa is English dominance in training, online resources, and professional networks. H3ABioNet data showed that English-only delivery increased uptake in Anglophone countries but limited participation from Francophone Africa (Aron et al. 2021b; Gurwitz et al. 2017). This shapes who enters training pipelines, which countries develop expertise, and who can participate in cross-border collaborations. Solutions require deliberate strategies such as translation and localization of core materials.

Training and education initiatives

Bioinformatics training in Africa has expanded considerably over the past decade, driven by recognition of workforce gaps and growing research demands (Karikari 2015; Karikari et al. 2015; Shaffer et al. 2019). New research centers and academic departments have increased participation and created additional training opportunities across the continent (Karikari et al. 2015).

Training embedded within funded research projects produces technical competence and employment pathways. In contrast, standalone workshops or coursework not linked to active research may generate skills that are difficult to sustain in the absence of funded positions. This challenge has previously been framed as a shortage of practical skills and depleting expertise across the continent (Chimusa et al. 2015).

H3ABioNet training model

During its operational period, H3ABioNet implemented a multi-layered training strategy tailored to institutions with varying infrastructure and expertise levels (Aron et al. 2021a, b; Mulder et al. 2016a). This included structured courses, workshops, and support for computational infrastructure at participating nodes, while addressing connectivity and resource limitations common in low- and middle-income settings (Choudhury et al. 2021).

A notable innovation was the continent-wide “Introduction to Bioinformatics” course, which used blended delivery and pre-recorded lectures to accommodate unstable internet access (Gurwitz et al. 2017). The course reached hundreds of participants across multiple countries and has since been adapted by several institutions for continued use.

Expansion and specialization

Training efforts have increasingly shifted toward specialization and research integration. Workshops and internships in areas such as population genetics and genetic epidemiology have complemented institutional degree programs (Siwo et al. 2015; Adoga et al. 2014). Infrastructure investments at selected universities enabled the establishment of dedicated bioinformatics laboratories and undergraduate courses (Mwita et al. 2023; Ahmed et al. 2019).

Post-H3ABioNet initiatives now emphasize advanced, project-based training embedded within research consortia. Programs such as AI-BOND provide specialized instruction in multi-omics data analysis and computational methods (Fongang et al. 2024), while the Eastern Africa Network for Bioinformatics Training (EANBiT) has adopted project-based learning models that prioritize hands-on research outputs (Kibet et al. 2024).

Despite this progress, continued expansion of training in artificial intelligence, high-performance computing, and next-generation sequencing analysis remains necessary, particularly when aligned with funded research opportunities (Mboowa et al. 2024). Sustained collaboration between African and international institutions continues to support knowledge transfer and capacity development (Akintola et al. 2024; Mulder et al. 2016a).

Regional variations and progress

Bioinformatics capacity across Africa remains uneven, concentrated in countries such as South Africa, Kenya, and Nigeria (Karikari 2015). These disparities reflect differences in infrastructure, institutional maturity, government investment, and unequal access to sustained research funding.

Southern Africa

Southern Africa, led by South Africa, represents the continent’s most established bioinformatics hub. The founding of the South African National Bioinformatics Institute (SANBI) in 1996 marked an early institutional milestone, supported by sustained government and external funding (Mohamed et al. 2021; Mulder et al. 2016b). This funding stability enabled expansion into university-based computational biology units, postgraduate training, and research programs, positioning South Africa as a continental leader in bioinformatics (Mwita et al. 2023; Mulder et al. 2016b).

West Africa

Bioinformatics development in West Africa accelerated in the early 2000s, led by Nigeria and Ghana through workshops, academic programs, and institutional initiatives (Mwita et al. 2023). Nigeria has since strengthened its position through national networks and institutional investments, including the Nigerian Bioinformatics and Genomics Network, aimed at addressing workforce and research needs (Tibiri et al. 2024; Bishop et al. 2014; Fatumo et al. 2014).

East Africa

East Africa’s progress has been shaped largely by regional collaborations and international initiatives. Kenya emerged early as a regional hub, supported by training programs and research partnerships (Mohamed et al. 2021). Investments through H3ABioNet enabled several universities to establish computational facilities and integrate bioinformatics into teaching and research (Mwita et al. 2023; Mulder et al. 2018; Ahmed et al. 2019).

Tanzania has engaged actively in regional and continental networks, including the Eastern Africa Network for Bioinformatics Training (EANBiT), which provides MSc-level training and institutional support across partner institutions (Kibet et al. 2024). Participation in professional networks such as the African Society for Bioinformatics and Computational Biology further supports collaboration and skills development (Sangeda et al. 2021).

Emerging platforms and connectivity

New bioinformatics platforms are emerging across the continent, though with varying levels of success. Initiatives such as the BurkinaBioinfo platform demonstrate both the potential for capacity development outside established hubs and the ongoing challenges of infrastructure limitations and staff retention (Tibiri et al. 2024). Despite constraints in computing resources and connectivity, these platforms are contributing to increased interest and participation in bioinformatics research.

Case study: Nigerian institute of genomics and public health

The Nigerian Institute of Genomics and Public Health (NIGPH), established in 2021 at the University of Ibadan, illustrates an integrated model combining laboratory genomics, bioinformatics, and public health research (Fatumo et al. 2020). Its development was preceded by more than a decade of funded research projects that generated genomic data and created demand for analysis capacity.

The institute emphasizes investigator-led research, partnerships with national health programs, and embedding bioinformaticians within funded projects. This approach has supported research outputs, genomic surveillance contributions, and employment pathways for trained bioinformaticians. The NIGPH model highlights the importance of linking training and infrastructure to consistent research investment.

Case study: Sydney Brenner institute for molecular bioscience

The Sydney Brenner Institute for Molecular Bioscience (SBIMB) at the University of the Witwatersrand represents a long-standing example of integrated genomics and bioinformatics development. Founded with sustained government and philanthropic support, the institute combines population genomics research, computational methodology development, and formal academic training (Mulder et al. 2016b; Schoonen et al. 2019).

Stable core funding, integration within university structures, and alignment with national research priorities have enabled long-term staff retention, postgraduate training, and internationally recognized research outputs. The institute has produced cohorts of bioinformaticians who now contribute to academic and research institutions within and beyond Africa (Soo et al. 2017).

Synthesis: common drivers of progress

Across successful African bioinformatics centers, progress is consistently associated with sustained research funding, integration with laboratory-based genomics, institutional stability, and opportunities for investigator-led research (Mulder et al. 2016a; Wonkam 2021). These elements create demand for analytical expertise and support sustainable career pathways, as demonstrated by the Nigerian Institute of Genomics and Public Health and the Sydney Brenner Institute for Molecular Bioscience (Fatumo et al. 2020; Soo et al. 2017).

Training and infrastructure are essential, but their effectiveness depends on being embedded within funded research programs that generate data requiring analysis (Mulder et al. 2016a; Wonkam 2021). When aligned with active research, personnel development and hardware investments reinforce long-term institutional growth rather than operating as standalone interventions.

Future directions and recommendations

Despite progress over the past decade and the emergence of new initiatives in the post-H3ABioNet era, significant work remains to realize Africa’s bioinformatics potential. Capacity and training opportunities have expanded, but access to research funding, infrastructure, and sustained institutional support remains uneven across the continent (Giovanni et al. 2022). Addressing these gaps requires shifting from supply-driven training models toward demand-driven capacity development linked to sustained research investment. Together, these persistent structural constraints form a self-reinforcing cycle (Fig. 3). Breaking this cycle requires a shift toward demand-driven bioinformatics capacity development, as conceptualized in Fig. 4.

Fig. 3.

Self-reinforcing cycle of bioinformatics capacity constraints in Africa, showing how limited expertise, training, infrastructure, and data generation interact to reduce research competitiveness and sustain capacity gaps

Fig. 4.

Demand-driven model for bioinformatics capacity development in Africa showing how sustained research funding and data generation drive training, infrastructure development, and long-term capacity growth

Aligning training with research demand

A central priority is aligning training investments with funded research programs that generate genomic data requiring analysis. Training embedded within active research environments where trainees work with real datasets and contribute to outputs supports both skill development and employment pathways.

Funding agencies could benefit from prioritizing integrated research–training awards rather than separate training or infrastructure grants. Universities and research institutions can strengthen sustainability by establishing stable bioinformatics career pathways within academic structures. Evaluation of training programs may also benefit from focusing on employment outcomes, publication productivity, and grant success rather than participation metrics alone.

Expanding strategic training areas

Building on existing initiatives, training expansion should focus on areas of growing research demand, including artificial intelligence, high-performance computing, next-generation sequencing, and multi-omics analysis (Mboowa et al. 2024; Vidanagamachchi and Waidyarathna 2024). Collaborative training models involving African and international institutions remain important for knowledge transfer and access to advanced technologies (Akintola et al. 2024; Mulder et al. 2017). To ensure equitable access, training content must be localized and diversified to include Francophone and Arabophone accessibility, as well as disability-aware materials, thereby expanding the addressable learner pool. However, training scale must be carefully calibrated to available research funding and employment opportunities to avoid mismatches between skills supply and demand.

Specialized capacity development

Specialized programs addressing emerging research areas are increasingly important, particularly in integrating multi-omics data and AI-assisted analytical approaches for disease identification (Vidanagamachchi and Waidyarathna 2024). Initiatives such as AI-BOND provide targeted training in multi-omics data analysis and computational methods (Fongang et al. 2024). Similarly, pan-African programs supporting malaria genomics are strengthening technical expertise and promoting integration of genomics into disease control strategies (Dada et al. 2024).

These initiatives illustrate the value of embedding training within research-driven environments.

Infrastructure and sustainability

Future infrastructure development should prioritize sustainability and alignment with research demand. Emerging platforms across the continent demonstrate both the benefits of improved computational capacity and the challenges of maintaining infrastructure without ongoing research funding (Fongang et al. 2024; Mwita et al. 2023). Experiences such as BurkinaBioinfo highlight the importance of linking infrastructure investments to funded research programs and long-term operational support (Tibiri et al. 2024).

Post-H3ABioNet transition

The completion of H3ABioNet funding marked a transition in African bioinformatics development. While the network significantly expanded training and infrastructure, sustainability outcomes have varied across institutions. Some nodes have integrated into national systems or university structures, while others have struggled without continued external support.

Lessons from this transition include the importance of institutional integration, diversified funding sources, alignment with national priorities, and development of service activities that support long-term sustainability. These insights have informed newer initiatives such as DS-I Africa and the African Institute of Bioinformatics (Mulder 2025).

Multi-stakeholder collaboration

Future progress depends on coordinated action among universities, governments, and research funders (Aron et al. 2021a; Akintola et al. 2024). National governments play a critical role, as demonstrated by South Africa’s sustained investment in bioinformatics infrastructure and research capacity (Mulder et al. 2016b). Collaboration frameworks can further strengthen knowledge exchange and regional integration (Tibiri et al. 2024; Dada et al. 2024). Sustaining these efforts will require continued investment, adoption of emerging technologies, and alignment with national research priorities.

Conclusion

Recent evidence suggests that Africa’s bioinformatics limitations stem less from personnel or infrastructure shortages and more from insufficient investment in African-led, data-generating research that sustains demand for analytical expertise (Mulder et al. 2016a; Wonkam 2021; Agamah et al. 2025). Findings from continental initiatives indicate that research funding, workforce development, and infrastructure operate as interdependent components, with training and infrastructure most effective when embedded within active research environments. These findings highlight the importance of coordinated investment linking research funding, institutions, and workforce development. This review is limited by the lack of continent-wide quantitative data to assess the relative influence of demand- and supply-side constraints, underscoring the need for future comparative studies.

Author contributions

All authors contributed equally in conceptualization, methodology, investigation, resources, writing; original draft, writing; review and editing and visualization.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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