Domains

Genomics
Single Cell & Transcriptomics
Metabolomics
Proteomics
Metagenomics
Epigenomics
Machine Learning
Systems Biology
Cloud Solutions
Database
Antibody Discovery
Extra

Domains we're active in

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Genomics

Genomics is the study of genes and chromosomes. Genomic studies have a wide range of purposes for example determining the structure of protein encoded, comparing genomic features in different species or study mutations that may occur in a person’s DNA. Genomes evolve over time, changing in sequence or size. Also more and more genomes are sequenced and made available to the scientific community and the public at large.

BISC consultants work with the genome version of choice and mostly handle “speed up” requests for variant calling, structural variation, copy number variation and join variant calling. We are also keen to dig deeper, integrate and expand this domain with multiple datasets and ever more powerful analysis methods.

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Transcriptomics

Connecting the genome to expression analysis. We all learned that genomes show what could happen and that transcriptomics (and proteomics) tells us what is happening at a certain point in time. The analysis of transcriptomes allows the identification of candidate genes and of expressed markers associated to traits of interest and is often a good starting point for your biomarker or assay signature. With the single cell transcriptomics application, transcriptomics has become top of mind again in the scientific community.

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Metabolomics

Metabolomics is the study of substrates and products in the cell, known as metabolites, which are influenced by both genetic and environmental factors. Once metabolic data is fully explored, it is important to carefully select the model method for metabolic data.

As relatively simple techniques like PCA (or Partial Least Squares Regression) are often not sufficient enough to reveal the subtle effects of the hidden patterns in the data more sophisticated statistical methods and machine learning can be used by BISC consultants.

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Proteomics

Using the large-scale study of proteins and proteomes, which can be applied to all living organisms, BISC explores proteomes from the overall level of protein composition, structure, and activity. The study of proteomes will often be complex due to the fact the proteome differs depending on cell type, timeframe and treatment. Furthermore there is a wide range of post-translational modifications which can also be studied.

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Metagenomics

Metagenomics is best known as the study of microbial communities in environmental samples, such as stool, sewage, soil, etc. It is being applied both in pharma/biotech and the Agro-industry. Data from metagenomics studies is often complex and requires in-depth bioinformatics and statistics knowledge for data interpretation and visualization. An interesting observation is that Metagenomics and Repertoire sequencing bare unexpected communalities.

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Epigenomics

Discovering the right epigenetic state often pre-defines pharmacological use and efficacy. So it’s best to know this upfront via fast, reliable and cost saving bio-informatic approaches. The epigenome consists of a variety of epigenetic modifications of the genetic material of a cell such as DNA methylation and histone modifications. This explains why the study of the epigenome has been gaining importance in biotech and pharma over the past years. The applications used to generate the complex data are for example bisulfite sequencing and ChIP-sequencing.

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Machine Learning

Find hidden patterns in existing data, public repositories combined with your R&D data using statistical, machine learning models. Based on a training dataset, an algorithm learns to identify patterns in the data and can make a number of predictions, for which it can be “rewarded” or “punished”. After numerous iterations, the mature algorithms can be applied to real-world data.

These underlying algorithms can take various forms, including decision trees, naïve Bayes classification, logistic regression, support vector machines, clustering algorithms, principal component analysis and many more.

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Systems Biology

By analysing holistic models the aim is to capture emerging patterns in cells, tissues and organisms by using for example network analysis and pathway analysis. Systems biology needs computational and mathematical analysis for modelling complex biological systems. The Human Genome Project is such an example of applied systems thinking. It clearly led to new ways of looking on genetic challenges and possibilities.

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Cloud Solutions

Biological data means big data, means massive storage and hence, flexible, parallel compute power. BISC follows best practices and guidelines for the set up and management of CloudEnvironments which are optimised for processing large chunks of biological data. This on-demand computing environment has the flexibility to run as fast and efficient as your project requires optimising time and cost.

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Database

All good analysis start with good data. Although it is a given, you can’t imagine how many analysis need to be rerun because of non-curated data being used as a feed to the analysis pipeline. Effective, good data means starting from raw data that is quality controlled, double checked and formatted into the best fitting database architecture.

All analysis benefit from this approach, especially techniques like machine learning that are extremely dependent on this database architecture. Because you will want to know upfront: Can the data be continuously added to improve my analysis? Will updates be logged? Which data is available for which algorithm? Do parameters and features join the database? Etc… BISC Global offers this expertise as it is vital to what we do, everyday.

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Extra

An extraordinary project? Please let us know as we like to use our creative mindset next to our logic and coding skills. Via regular follow-up meetings between you, the customer, our consultants, BISC Global managers and academic experts BISC ensures project qualification and execution aiming for highest customer satisfaction.

Our consultants are highly skilled in multiple domains, developing custom solutions in areas of algorithm development, data mining, image processing, (un)supervised learning, pattern recognition, deep learning, neural network development and others. We apply the highest industry standards in Information Technology to your needs in Computational Biology.

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Antibody Discovery

An extraordinary project? Please let us know as we like to use our creative mindset next to our logic and coding skills. Via regular follow-up meetings between you, the customer, our consultants, BISC Global managers and academic experts BISC ensures project qualification and execution aiming for highets customer satisfaction.  

Our consultants are highly skilled in multiple domains, developing custom solutions in areas of algorithm development, data mining, image processing, (un)supervised learning, pattern recognition, deep learning, neural network development and others. We apply the highest industry standards in Information Technology to your needs in Computational Biology.

contact us