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Our Mission

At BionomeeX, we are dedicated to bringing the world of scientific research into a new area of excellence by  making possible the use of advanced artificial intelligence tools. Our fusion of expertise in Biology and AI empowers us to delve deeper into challenges within biology, medicine, and environmental studies. We specialize in delivering tailored AI solutions that are, rapid, and cost-effective, to facilitate scientific advances in health, biology and ecology. 

We meticulously craft tailored products and services that cater specifically to the demands of research and researchers including computer vision image analysis, segmentation, and detection.

As your partner, we offer unwavering support to academic researchers, guiding them from conceptualization to software development and design.

Join BionomeeX on this journey, where inventions evolve into innovations, propelling scientific progress in computational workflows using innovative inference methods, statistical mapping, genotype variants, large-scale data sets, and beyond in the vibrant scientific community of Montpellier.

Discover the power of our solutions, mixing deep learning, genomics, and multimodal datasets (images, sequences, knowledge), paving the way for unparalleled discoveries in scientific research in Montpellier and across the globe.

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BionomeeX: A skilled team advancing genetic research and environmental understanding. Our geneticists specialize in Chromosomal dynamics, Replication, and traits like Homozygous, Recessive, and Heterozygous characteristics. With expertise in genetic markers and a focus on a large number of data points, we unravel complexities like Polygenic inheritance, estimating multifactorial influences in developmental processes. Join us on the forefront of genetic research, where our team decodes correlations, pleiotropy, and hereditary coefficients in collaboration within consortia.
AI revolutionizes biology, propelling research into new frontiers. From decoding genetic intricacies to unraveling genotype-phenotype relationships, AI's impact is transformative. In Genome-wide Association Studies, AI analyzes vast datasets, clusters genetic variants, and enhances understanding across diverse biological domains. This innovative technology drives breakthroughs in heredity, reproduction, and the study of model organisms. Through imputation, estimation, and coefficient calculation, AI provides insights into ancestral roots and complex trait deviations, reshaping the landscape of biological research

Innovation

At the heart of our identity lies innovation an unrelenting pursuit to redefine technological frontiers and craft groundbreaking AI solutions that revolutionize the realms of medicine, biology, and the environment.

Revolutionizing genetic research, our cost-effective AI solutions provide affordability without compromising quality. Researchers benefit from efficient data analysis, streamlined collaboration, and precise insights into genotype-phenotype correlation. Our tools cover model organisms, inbred studies, and Genome-wide Association Studies, offering valuable data on wild-type traits and genetic markers. With clustering and Plink analysis, we decode genetic variance and trait expression patterns, delivering impactful insights without excessive costs. Join the cost-effective revolution, empowering geneticists for breakthroughs in research.

Cost-effective solutions​ 

We're committed to democratizing access to cutting-edge tools by offering cost-effective solutions, ensuring that these advancements are affordable for all. Our dedication lies in making groundbreaking innovations affordable, empowering wider access to transformative technologies.​

In the realm of eco-friendly AI startups, we prioritize sustainability without compromising performance. Our innovative solutions employ eco-conscious practices, utilizing advanced statistical methods and genetic mapping for efficient analysis. With a focus on collaborative efforts within consortia, we streamline the study of model organisms and diverse genetic strains. From precise sequencing to exploring additive genetic variance, our startup leads in sustainable genetic research. Embrace a greener future with us as we pioneer eco-friendly AI solutions, combining environmental responsibility with cutting-edge insights

Eco-friendly start-up​

At our eco-friendly startup, a steadfast commitment to eco-responsibility,guided by the principles of Frugal AI, steers every action

we take. Principles of Frugal AI emphasizes efficiency and sustainability. We are committed to bringing this innovative, environmentally-friendly solution to your research laboratories with ease.

 


 

Let us empower you achieve your vision


Our mission is to support you whether you're exploring uncharted territories or refining existing projects. Our tools enable phenotype prediction in diverse model organisms. We delve into environmental factors, pathways analysis, and offer insights into biomedical discoveries and more. Our tailored AI solutions enhance methodologies, accelerate timelines, and drive towards breakthroughs in medicin, biology and ecology. 

Our advanced AI solutions including Computer vision act as your guiding companion throughout the research journey. We value the human touch in research. 
Our solutions aren't just a tool; they are collaborative partners, amplifying your efforts while remaining attentive to your unique needs. We're here to listen, understand your ideas, and work hand in hand to transform them into impactful solutions that drive scientific advancement.




Artificial Intelligence (AI) is transforming genetic analysis, accelerating advancements in understanding genetic traits and inheritance patterns, AI facilitates comprehensive analyses. It examine easily complexities such as single nucleotide polymorphisms (SNPs), haplotypes, and heritable traits, aiding geneticists in deciphering inheritance mechanisms and cohort-based studies. AI-driven tools streamline large-scale genetic analyses, decoding the intricacies of genomic data for insights into mutation, ancestry, and transcription regulation. Its capabilities in meta-analysis and case-control studies propel breakthroughs in epidemiology and metabolic research, offering a deeper understanding of genotype-phenotype relationships and inherited traits. Through AI's adaptive learning, researchers unlock the potential to explore diverse genetic landscapes, providing a dynamic approach in genetic analysis and reshaping our understanding of organisms and genetic diversity.
Biology 


Our artificial intelligence tools, developed by and for researchers in biology, offer unparalleled expertise in simplifying the exploration of all types of data. Using our advanced image analysis methods provides a fresh perspective on your various research projects.

The use of our image analysis tools provides abundant information concerning, notably, the physiological properties of cells (such as their phase in the cell division cycle, health status), as well as protein-protein interactions derived from microscopy images.
We also offer a genomic analysis tool providing expertise on genetic variation, polymorphism, and phenotypic analysis that may be linked to pathological traits. 

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AI in Genetics Innovative solutions are essential to reshaping our understanding of genetics by navigating the intricate landscape of quantitative traits, allele frequencies, and recombination patterns. As an indispensable tool, AI delves into analysis of single-gene studies, allelic variations, and genotypic diversities, shedding light on the variance. AI's applications extend to elucidating changes in expression on molecular and metabolic pathways, exploring the subtleties of natural selection, and dissecting population structures.With AI analyzes of diploid organism, evaluates the Hardy-Weinberg equilibrium, and contributes to evaluates the impact on genetic of environmental changes.
Medicine 

 

Thanks to our advances in biology, the expertise of BionomeeX can now accelerate the time of medical diagnosis while reducing their complexity of understanding. We cover, in a non-exhaustive way, the analysis of medical images (MRI, radiology, ultrasound, scanner) as well as the in-depth study of the relationships between genomes and pathologies. We therefore provide tools adapted to fundamental research in medicine as well as to clinical research projects that may be in advanced stages of clinical trials.

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We pioneer cutting-edge solutions for enhanced environmental understanding and a sustainable future. Proficient in quantitative genetics, our analysis spans key environmental traits, offering comprehensive assessments to guide eco-conscious decisions. Expertise in tracking animal populations, coupled with field-friendly tools and software for data analysis, contributes to holistic environmental evaluations. Through 3D printing, we advance sustainable practices and informed decision-making, while excelling in thermal imaging mapping and leveraging aerial imagery for precision in environmental insights. Our approach integrates genetic aspects, including Locus, Polygenic traits, Population Genetics, and Bioinformatics. Explore the intricacies of Hapmap, genetic architecture, Alleles, and complex traits, as well as factors like Genetic linkage and Genome-wide association studies. With a focus on Additive effects and a consideration for a large sample size, our solutions redefine the landscape of environmental analysis and contribute to a sustainable future.
Environment 


Our AI solutions enhance environmental understanding for a sustainable future. Indeed, we enable the intuitive analysis of key environmental features (such as population monitoring, species enumeration within a target area, soil physical characteristics), thereby assisting researchers in making environmentally respectful decisions. Furthermore, we develop project-specific tools, exploitable under field conditions, thanks to 3D printing. Similarly, regarding field studies, we excel in thermal imaging analysis, cartography, and aerial imaging for precise field diagnostics, thus advancing environmental perspectives and decision-making.

 

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Our AI projects

 

Revolutionize your data labeling process with HITLOOP, where an innovative AI-powered method takes the lead. Seamlessly streamline the workflow by importing and annotating your data, initiating the training of an initial model on labeled data. This model then predicts labels for the remaining dataset, a process enriched by human validation. The cycle repeats through iterative retraining, consistently elevating the model's accuracy. HITLOOP's approach integrates AI-driven efficiency into data labeling. Users kickstart the process by importing and annotating a subset of their data. The initial model, trained on labeled data, predicts labels for the remaining dataset. Human validation refines these predictions, driving iterative retraining that continuously enhances the model's accuracy. Experience a data labeling revolution with HITLOOP's dynamic and efficient AI-driven methodology
HixLoop


HixLOOP revolutionizes the classification and analysis of imaging data through an AI-powered method.

Initially, users begin by importing their data and annotating a small portion of it. This allows training of an initial AI model on classified data to predict annotations for the rest of the dataset. These predictions are always subject to human validation, refining the AI model through iterative retraining.

This continuous process gradually improves the model's accuracy and optimizes the data labeling process. Subsequently, once the model is trained, users can simply decide which data they want to analyze with this model and let the AI generate the various annotations. Each result can then be validated or adjusted by the user to be as specific and precise as possible while significantly saving analysis time.

Learn about Hixloop


Our Genomics projects

 

Next Gen GWAS


The advent of Genome-Wide Association Studies (GWAS) has drawn attention to the concept of "missing heritability," which has a profound impact on genetics and the studied phenotypes. Conventional GWAS models face efficiency problems, taking years to fully explore combinatorial epistatic interactions. 

Our tool NEO introduces an innovative modeling technique capable of evaluating billions of genetic variant interactions. Our research indicates that a portion of the missing heritability can be elucidated using this method, significantly refining phenotypic predictions. With NEO, we explore the influence of single nucleotide polymorphisms (SNPs) on genetic and phenotypic interindividual variation. 

By analyzing population structure and kinship links, our tool sheds light on phenotypic variation in various plant, animal, and human organisms. It identifies polymorphic genotypes, studying their connection with mutations present in the genome. The NEO tool enables researchers to explore the complex landscape of genetic studies and facilitates the interpretation of scientific results by clearly and concisely linking the possible causes of specific phenotype appearance. It provides invaluable data on genetic variability and phenotype transmission, including information on offspring metabolic pathway adaptation in response to environmental factors.

Learn about NGG

NEO revolutionizes genetic studies by addressing the 'missing heritability' challenge in Genome-wide Association Studies (GWAS). Unlike conventional models, NEO employs an innovative technique, efficiently evaluating billions of genetic variant interactions, significantly refining phenotype predictions. This tool delves into multiple loci, linkage disequilibrium, and haplotype patterns, surpassing Mendelian genetics to uncover quantitative trait loci and epistasis interactions. NEO analyzes population structure, identifying polymorphic genotypes and their link to deleterious mutations, providing valuable insights into genetic variability and phenotype transmission. Empowering researchers, NEO facilitates the interpretation of scientific results, shedding light on the intricate landscape of genetic studies and the adaptation of metabolic pathways in response to environmental factors.
Luciol, an avant-garde software, navigates complex epistatic interactions in massive 2D GWAS datasets. With a user-friendly interface, it empowers biologists to explore over 60 billion interactions effortlessly. This tool enables geneticists to analyze causal factors, gene expression variations, and marker detection. Luciol's results are correlated with DNA sequence changes, allelic diversity, and linked to QTL mapping. With robust statistical power, it excels in inferring Mendelian inheritance, elucidating model organism relationships, and providing insights into metabolic processes. Luciol is a powerful platform reshaping genetic analysis and unraveling the complexities of epistatic interactions.
Luciol

 

Luciol, an avant-garde software, is designed to navigate the expansive realm of epistatic interactions, handling massive 2D GWAS data extending into terabytes. Featuring a user-friendly 'plug and play' interface, Luciol caters to biologists, enabling effortless exploration of intricate epistatic variations. Gain insights into over 60 billion interactions with Luciol's intelligent layered visualization. 

This tool allow geneticists to analyze causal factors and variations in gene expression and marker detection.  Our results can be associated with changes in DNA sequence, allelic diversity within a population, and sometimes, they can be linked to QTL mapping.

With statistical power, Luciol performs to infers Mendelian inheritance, elucidating relationships in model organisms, handling deletions, and offering insights into metabolism.


Learn about Luciol

Make the right choice

Tailored Solutions


Understanding your needs is paramount. We craft bespoke AI solutions tailored precisely to meet your unique requirements. From conceptualization to implementation, we stand by our partners, ensuring their expectations are not just met but exceeded..

Competitive Pricing


Experience our AI solutions at highly competitive rates, setting unparalleled standards in the market. We prioritize affordability while upholding top-notch quality in our offerings.

Eco-Responsible Commitment  


Our dedication to eco-responsibility drives our project selection, focusing solely on initiatives aligned with our environmental values, aiming for a tangible impact on the planet.

Project Support & Availability


Count on our dedicated project support and easily accessible teams to guarantee seamless project execution. Your success stands as our primary commitment.



Join us to make a Future where AI Empowers Positive Transformation, Nurturing Benefits for Individuals and Communities Worldwide!

​Contact us

Our Partners


Agro Valo, our collaborative startup incubator, is a thriving hub for innovative ventures in genetic research. Focused on exploring sequenced data, linkage analysis, and quantitative trait loci, Agro Valo supports startups utilizing advanced technologies like Illumina for Genome-wide Association Studies. Within this ecosystem, startups benefit from resources for studying meiosis, segregation, and progeny, along with support for exploring mutants, discrete genetic correlations, and parental relationships. Agro Valo's commitment to fine mapping, linear models, and addressing genetic heterogeneity ensures startups receive robust support in biochemical and microbial realms. This collaboration provides startups with a solid foundation for success in the dynamic landscape of genetic innovation.
AXLR offers businesses a range of services spanning Health & Biotechnology, Agronomy, Ecology & Environment, and Mathematical, Computer, and Systems Physics. In the realm of genetics, AXLR provides expertise in genotype-phenotype correlations, genetic markers, and quantitative trait loci analysis. Services extend to exploring mutants, genetic correlations, and the onset of traits through advanced technologies like Genome-wide Association Studies. Within AXLR, businesses receive support in fine mapping, addressing genetic heterogeneity, and utilizing linear models to understand genetic effects. Services cover aspects of genetic research, including penetrance, inferred data analysis, and exploration of heterosis and additive genetic effects. AXLR's offerings encompass genetic factors, specificity studies, and applications in fields like schizophrenia, receptors, epigenetics, molecular markers, and epistatic effects. The tailored services ensure a comprehensive approach to genetic innovation for businesses seeking insights into genotypes, phenotypes, and unrelated genetic factors.
BionomeeX collaborates with the University of Montpellier, a leader in genetic research. This partnership focuses on genetic markers, genotype-phenotype correlations, and quantitative trait locus analysis. Advanced technologies, including Genome-wide Association Studies, are utilized for exploring mutants and genetic correlations. The collaboration also encompasses fine mapping, genetic heterogeneity, linear models, penetrance, inferred data analysis, and investigations into pedigrees, pairwise relationships, epigenetics, deletions, and the implications of genotypes and phenotypes. Together, BionomeeX and the University of Montpellier drive advancements in genetic research, contributing to replication studies, pleiotropic effects, stratification, normal distribution, and simulated scenarios. This collaboration strengthens the foundation for groundbreaking discoveries in genetics.
The BIC (Business and Innovation Centre) in Montpellier is an exceptional catalyst for innovative enterprises, providing crucial support across various sectors, including genetic research. This collaborative hub fosters ventures exploring genetic studies, genotype-phenotype correlations, and genetic markers. The BIC facilitates advanced technologies like Genome-wide Association Studies for the exploration of mutants, genetic correlations, and traits. Enterprises at the BIC benefit from resources for fine mapping, genetic heterogeneity, linear models, and other genetic effects. The collaboration extends to studying pedigrees, epigenetics, deletions, and the implications of genotypes and phenotypes. In partnership with the BIC, enterprises gain valuable insights into genetic aspects, contributing to advancements in replication studies, pleiotropic effects, and other phenomena. The BIC stands as a crucial collaborator, supporting innovative enterprises in genetic research and contributing to the broader landscape of scientific discovery.
The CNRS (Centre National de la Recherche Scientifique) is a pillar of scientific excellence, offering vital support across diverse fields, including genetic research. Implicitly, the CNRS collaborates with scientists, fostering studies in genotype-phenotype correlations, genetic markers, and advanced technologies like Genome-wide Association Studies. As a driving force, the CNRS supports ventures exploring mutants, genetic correlations, and traits, contributing to a broader understanding of genetic phenomena. Within the CNRS framework, enterprises access resources for fine mapping, genetic heterogeneity, linear models, and other genetic effects. The collaboration extends to studying pedigrees, epigenetics, deletions, and the implications of genotypes and phenotypes. In partnership with the CNRS, ventures gain valuable insights into genetic aspects, contributing to advancements in replication studies, pleiotropic effects, and other phenomena. The CNRS stands as a pivotal collaborator, supporting innovative enterprises in genetic research and enriching the scientific landscape with new discoveries.
CEA plays a pivotal role in scientific and technological research, contributing significantly to genetic research. Although not explicitly mentioned, CEA collaborates with scientists, fostering studies in genotype-phenotype correlations, genetic markers, and advanced technologies like Genome-wide Association Studies. As a central figure, CEA supports ventures exploring mutants, genetic correlations, and traits, contributing to a broader understanding of genetic phenomena. Within the CEA framework, enterprises gain access to resources for fine mapping, genetic heterogeneity, linear models, and other genetic effects. The collaboration extends to studying pedigrees, epigenetics, deletions, and the implications of genotypes and phenotypes. In partnership with CEA, ventures receive valuable insights into genetic aspects, contributing to advancements in replication studies, pleiotropic effects, and other phenomena. CEA plays a pivotal role as a collaborator, supporting innovative enterprises in genetic research and enriching the scientific landscape with new discoveries.