Python to unravel cancer drug target proteins and drug resistance mechanism analysis



This talk is aimed to analyse the network of proteins inside a cancer cell and identify cancer drug targets. Small network of 83 proteins and 183 interaction in MAPK pathways is analyzed. After the preliminary identification of drug targets, we do parallel local drug resistance analysis using python function.

This talk gives the idea to approach any real life problem by using python. Furthermore, techniques to embed the domain knowledge with the network analysis approach. Global and local iterative analysis procedure to divide & conquer the whole problem by top down approach.


• Construction of network of MAPK pathways. • Network pattern revealing with simple metric analysis using python Networkx package. • Biological process of each protein assigned in the network of MAPK pathways using Matrix. • Topological and functional attributes of the network based cluster identification. • Local drug target resistance analysis by calling python function parallelly


No need of any pre-requisite. The content will be self contained.

Content URLs:

Slides for pycon2019

Speaker Info:

MD Aksam VK working as Data Scientist at ZettaLabs. Hands on implementation of python code to Statistical, Optimization, Machine Learning and Artificial Intelligence based analysis for 5 yrs. Having experience in building own metric called Alternate Centrality for the Network Analysis ( . Furthermore, devised and implemented the clustering algorithm in the python for cancer drug target identification (

Started my career as Master’s in Mathematics and got exposed to biological problems while doing summer intern on “Mathematical Modelling of Cardiovascular System”. Followed with Project Assistant work on “Computational analysis and coding for numerical methods” Indian Institute of science (IISC), SUPERCOMPUTER EDUCATION AND RESEARCH CENTER (SERC lab) Banglore

In my Ph.D., I explored Network Biology to reveal cancer drug target identification. Aiming to understand the hidden pattern of biological network and its contribution under pathological condition. The computational framework is built to Integrate network data, gene expression, and protein structural data to identify potential drug targets and drug resistance mechanism.

Reviewer in scientific journals : 1. IEEE Journal of Biomedical and Health Informatics (IEEE) 2. Proteomics (WILEY) 3. International Journal of Nano and Biomaterials (Inderscience)

Speaker Links:

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poster presentation on 16th International Conference on Systems Biology (ICSB) 2015 Natioinal university of singapore , Biopolis, Singapore.,

Id: 1343
Section: Scientific Computing
Type: Talks
Target Audience: Intermediate
Last Updated: