Bioinformatics the way biology wants it to be

Our principles

For more than 10 years we are working on biomedicine covering numerous complementary fields from Computer Science and Systems Biology. Our contrast of knowledge is governed by two principles:

  1. data quality is the angular stone of the discovery process in science
  2. data quality is as high as the level of understanding its properties

Our vision

Utilizing the modern arsenal of bioinformatics tools to accelerate, simplify and standardize translational research, drug discovery, clinical trials and precision medicine.

Assisting scientists to easily discover and refine hypotheses by investigating the relationships between genetic and phenotypic data for cohorts of patients, and to assess their analytic results in the context of published literature and their personal work.

Our story of success

The success behind all our previous projects relies on three factors:

  1. design systems to be used by scientists involved in any biomedical domain without the need for specific bioinformatics or mathematics knowledge,
  2. provide tools that have the ability not only to read data, but also interpret data properties and understand the relationships between them,
  3. build solutions using standardized pipelines for data management, integration and analysis.

IMPACT

Our vision of science, focusing on making bioinformatics easily accessible by more scientists, led us to join forces with the European Society for Clinical Cell Analysis (ESCCA) and start implementing the next big thing.

After a year of preliminary research, we are now actively developing our latest project: Interdisciplinary MultiOMIC Project to Advance Crossanalysis in Translational Research (IMPACT).

With this initiative, we aim at promoting innovative technologies in data management and provide an automated cloud solution for cross-analysis of OMICs and clinical data.

faster
100%
easier
100%
safer
100%

Who we are

Iannis Drakos

Iannis Drakos

The informatics scientist

I am a software engineer who discovered the fascinating world of biomedical research and his passion led him to get a PhD in medicine. Focusing on data science for 15 years, I managed to accumulate some well distributed expertise among various fields, mainly: data management, integration, analysis, clinical coding, eCRF, database design, information systems and bioinformatics.

Nicolas Derian

Nicolas Derian

The data scientist

A decade long academic experience allowed me to acquire a wide range of skills: a solid technical base, a deep knowledge in fundamental biology and a strong expertise in bioinformatics and biostatistics. After working as an engineer in research labs, and completing a PhD in Systems Biology, I am building further on this background to develop personal and collaborative biomedical projects.

"Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away."

ANTOINE DE SAINT-EXUPÉRY

Informatics.bio by numbers

petabytes analyzed
Lines of code
Projects completed
Files parsed

Services

Data Analysis

Data Analysis

Descriptive statistical analysis / Supervised and unsupervised analysis / Statistical and mathematical models / Molecular signatures and Biomarkers discovery

Consulting

Consulting

Fundraising / Project authoring / Experiment design / Analysis strategy / Bioinformatics / Publication / Data Curation / Clinical Coding / eCRF / IT / Data safety

Bioinformatics

Bioinformatics

We offer bioinformatics solutions that can make a difference to your work-life. Standardized and automated pipelines using the latest open-source solutions, having in mind that the end-user must work easier, faster and with higher productivity.

eCRF/Data capture

eCRF/Data capture

To produce strong results, you need reliable data. We can provide high quality and user-friendly services for all your eCRF and data capture needs: from design and implementation to regulatory auditing and approval.

Data Management

Data Management

Data curation / Database design and implementation / Data integration / Data Management / Data mining / Data safety / Clinical coding / eCRF design and implementation

Cytome

Cytome

We offer access to powerful tools for flow- and mass-cytometry for data management and data analysis, including automatic gating and cell population annotation.

Genome

Genome

Our services include consulting on chromosomes and genes analyses performed with comparative genomic hybridization array and next generation sequencing.

Transcriptome

Transcriptome

We possess strong experience in molecular signature discovery using unsupervised analysis methods and random-forest models on transcriptomic data from PCR-derived technologies, microarray and next generation sequencing.

Microbiome

Microbiome

Next generation sequencing offers the opportunity to study microbiota; we provide advice on the experience plan, bioinformatics support and data analysis for your microbiome projects.

Proteome

Proteome

Our competences are covering molecular signature discovery from sera using fluorescent methodologies or mass-spectrometry.

From the Blog

Integrating nanomedicine and imaging

A publication written by Pérez-Medina C, Hak S, Reiner T, Fayad ZA, Nahrendorf M and Mulder WJM, 29 November 2017.

Biomedical engineering and its associated disciplines play a pivotal role in improving our understanding and management of disease. Motivated by past accomplishments, such as the clinical implementation of coronary stents, pacemakers or recent developments in antibody therapies, disease management now enters a new era in which precision imaging and nanotechnology-enabled therapeutics are maturing to clinical translation.

Read More

Animal Models in Translational Research: Rosetta Stone or Stumbling Block?

A review written by Bolker JA in Bioessays, 20 October 2017.

Leading animal models are powerful tools for translational research, but they also present obstacles. Poorly conducted preclinical research in animals is a common cause of translational failure, but even when such research is well-designed and carefully executed, challenges remain. In particular, dominant models may bias research directions, elide essential aspects of human disease, omit important context, or subtly shift research targets.

Read More

A framework for the design, conduct and interpretation of randomised controlled trials in the presence of treatment changes

A publication written by Dodd S, White IR and Williamson P in Trials, 25 October 2017.

When a randomised trial is subject to deviations from randomised treatment, analysis according to intention-to-treat does not estimate two important quantities: relative treatment efficacy and effectiveness in a setting different from that in the trial. Even in trials of a predominantly pragmatic nature, there may be numerous reasons to consider the extent, and impact on analysis, of such deviations from protocol. Simple methods such as per-protocol or as-treated analyses, which exclude or censor patients on the basis of their adherence, usually introduce selection and confounding biases. However, there exist appropriate causal estimation methods which seek to overcome these inherent biases, but these methods remain relatively unfamiliar and are rarely implemented in trials.

Read More

Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness.

A publication written by Seymour CW, Gomez H, Chang CH, Clermont G, Kellum JA, Kennedy J, Yende S and Angus DC in Critical Care, 18 October 2017.

All of medicine aspires to be precise, where a greater understanding of individual data will lead to personalized treatment and improved outcomes. Prompted by specific examples in oncology, the field of critical care may be tempted to envision that complex, acute syndromes could bend to a similar reductionist philosophy-where single mutations could identify and target our critically ill patients for treatment. However, precision medicine faces many challenges in critical care.

Read More

Classical Statistics and Statistical Learning in Imaging Neuroscience

A review written by Bzdok D in Frontiers in Neuroscience, 6 October 2017.

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression.

Read More

Benefits of Outsourcing Strategy and IT Technology in Clinical Trials

A review written by Stamenovic M and Dobraca A in Acta Informatica Medica, 25 September 2017.

Aim of this paper is to describe some of models of outsourcing (numerous and response to different types of risks and increment of quality is based on individual problem and situation). Defining whether to outsource or not and whether to build or buy new information technology (IT) is question for contract research organization (CRO) and Pharma companies dealing with clinical trials, so the aim of this paper is to show business model that could make process of decision making less time consuming, less segmented and more efficient.

Read More

Our next event

Our next event will take place at the European Society for Clinical Cell Analysis (ESCCA) annual conference.

Join us this September in the beautiful city of Thessaloniki, Greece and get updated about the latest developments in translational research information systems and multi-OMICs analysis.

Get more info at the conference website.

Testimonials

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