Dr. Alpha Tom Kodamullil


Alzheimer’s disease Knowledge Map:

Alzheimer disease (AD) model represents the pathological mechanisms in neurons in human brain as well as some additional evidences from mouse and rat. This model includes different pathways and hypotheses around AD. This model integrates knowledge from research articles, reviews and various databases using Biological Expression Language (BEL). This knowledge map is comprised of different entities like proteins, genes, bioprocesses, drugs, miRNAs, SNPs, epigenetic factors and so on.

AETIONOMY – Developing a “mechanism-based taxonomy” of Alzheimer´s and Parkinson´s Disease

The AETIONOMY concept foresees a primary role of the taxonomy in
i) describing and organising the indication-specific data in the data cube, in
ii) linking the data to disease models that are based on causal and correlative relationships and in
iii) support of reasoning over the knowledge that is explicitly represented in related ontologies or knowledge-based disease models.

Post-Traumatic Stress Disorder (PTSD) Knowledge Map:

PTSD Knowledge Map bring together research on clinical symptoms, biomarkers, genetic variation, epidemiological studies and many other factors deemed relevant for PTSD. It includes easy-to-use interactive visualizations for people to search vast data in an accessible manner.

PTSD Biomarker Meta-Database:

PTSD DB catalogs a meta- analysis of clinical data and links it with the mechanistic models. The database was developed as result of a collaboration effort by Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Cohen Veterans Bioscience.

Trauma Related Brain Disorders (TBRD) Knowledge Map:

TBI Knowledge map aims to build an integrated disease model based on Biological Expression Language (BEL) from a selected corpus of 500 research and review articles. This model contains the core mechanisms of Trauma Related Brain Disorders (TRBD). This project also aims to build shared sematic platform in the area of TBRD.

COMMITMENT – Integrative machine transfer learning for psychiatric diseases

The goal of the project "COMMITMENT – Modeling Comorbidity Processes by Integrative Machine Transfer Learning for Psychiatric Disorders" is to develop a computer-based systems medicine framework that enables clinically meaningful stratification of psychotic disorders and identification of biological processes. Comorbidities are also taken into account.

IDSN – Integrative Data Semantics for Neurodegenerative Research

In the BMBF-funded IDSN project, Fraunhofer SCAI, the German Center for Neurodegenerative Diseases (DZNE) and Bonn University Hospital (UKB) worked on improving the early detection of dementia. To do this, they analyzed clinical and research data in an overall view.  The information extraction approaches developed can be used by clinics. The semantic linking service for data integration from sources in the field of neurodegenerative diseases is available to public institutions and the pharmaceutical industry.

COPERIMOplus – COronavirus PErsonalized RIsk MOdels:

The participating institutes want to use rational, data-driven modeling to enable individual risk assessments in order to improve the prognosis of disease progression and to optimize personalized therapies and their evaluation based on objective, standardized criteria. Thus, the project contributes to making it possible to live with the pandemic and return to economic and social normality.

VirtualBrainCloud – Personalized Recommendations for Neurodegenerative Diseases:

In the VirtualBrainCloud project, Fraunhofer SCAI is working with 16 European partners on a cloud-based IT platform that enables the simulation of communication paths in the brain. The individual simulation of patient brains supports physicians in finding the right diagnosis and therapy for people with neurodegenerative diseases. This is usually difficult because the course and symptoms of diseases such as Alzheimer's are often very different. With this platform, it will be possible to record the state of health of the brain with little effort. Regular routine examinations will enable physicians to detect and treat Alzheimer's disease at an early stage.

Theses Supervision:

Dr. Reagon Karki
A bridge between data and knowledge world to better understand Alzheimer Disease and Type 2 Diabetes comorbidity and quantify underlying causal mechanisms, PhD-Thesis (2021)

Daniel Domingo-Fernandez:
Multimodal Mechanistic Signatures for Neurodegenerative Diseases (NeuroMMSig): a webserver for mechanism enrichment
Master Thesis in Life Science Informatics, University of Bonn (2016)

Afroza Khanam Irin:
Strategies for the representation of Epigenetics Information using Computational Modelling in Neurodegenerative Diseases
Master Thesis in Life Science Informatics, University of Bonn (2015)

Reagon Karki:
New roads towards understanding idiopathic diseases: comorbidity modelling aimed at identifying mechanisms shared between Alzheimer’s disease and Type 2 Diabetes Mellitus
Master Thesis in Life Science Informatics, University of Bonn (2014)

Mohammad Asif Emran Khan Emon:
Using drugs as Molecular Probes: enabling a “Chemical Biology” Approach in Molecular Systems Biology of the Brain
Master Thesis in Life Science Informatics, University of Bonn (2014)