Vamika Karn – Uncover the Biotech Prodigy Shaping the Future of Cancer Research and Machine Learning

Print Friendly and PDF

Curriculum Vitae

Introduction: Vamika Karn is a dedicated professional with a Master’s in Technology in Biotechnology. She has a strong research background and expertise in various aspects of biotechnology, including gene regulation, multi-omics data integration, and machine learning.

Employment Details

Aug 2022 – Jan 2024: Research Assistant at Daksh Foundation:

  1. Assisted in providing hands-on training to students in Protein Structure Prediction and Molecular Docking.
  2. Conducted research work on Parkinson’s disease.
  3. Conducted a literature review on Machine Learning algorithms for diagnosing Parkinson’s disease.

Jan 2024 – June 2024: Dissertation Trainee at Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Mumbai:

  1. Gene regulator network analysis of cancer-specific biomarkers of clear cell renal cell carcinoma.
  2. Utilized tools such as R, TCGA, and Machine Learning.
  3. Worked on Multi-Omics Data Integration, Network Inference, Network Simulation, Cox Regression, and Survival Analysis.

Basic Academic Details

Course Name of Institute Passing Year Percent/CGPA
M. Tech Biotechnology Amity Institute of Biotechnology (Amity University Mumbai) 2024 [hidden]
B. Tech Biotechnology Amity Institute of Biotechnology (Amity University Mumbai) 2022 [hidden]
ISC (XII) Carmel High School 2016 [hidden]
ICSE (X) Carmel High School 2014 [hidden]

Internships

  1. Quantium Data Analytics Internship (August 2024): Data Preparation, Experimentation and Uplift Testing, Analytics and Commercial Application.
  2. Summer Intern at Centre for Computational Biology & Translational Research, Amity (July 2023-Aug 2023): Worked on the identification of high-risk genes in Parkinson’s disease.
  3. Project Student at Centre for Computational Biology & Translational Research, Amity University Maharashtra (Jan 2022-May 2022): Performed structural and translational analysis of embB receptor and its mutants for MDR-tuberculosis.

Skills

Languages: R, Bash, Python

Version Control: Git, Github

Tools and Softwares: GATK, bcftools, samtools, bamtools, STAR, StringTie, Kallisto, PyMOL, AutoDock, Desmond, GROMACS, Chimera, Discovery Studio, Cytoscape

Methods and Concepts: Multi-Omics Data Integration and Analysis, Machine Learning, Cloud Data Engineering, Basics of Data Science & Analysis, Gene set enrichment (GSEA), Gene Ontology enrichment, Differential Gene expression (DESeq2, EdgeR), Dimensionality reduction (t-SNE, PCA, hierarchical clustering), Sequence Assembly & Alignment (BWA/STAR/BowTie), Gene abundance estimation (HTSeq-counts), Survival Analysis, Mutation and genetic aberration analysis (VarScan2, CNVkit, ClinVar, COSMIC), Statistical Analysis (Pearson/Spearman correlation, Student t-test, Wilcox rank sum test, ANOVA), Protein Structure Prediction & Analysis (I-TASSER, Swiss-Model, ProSA, PDBsum), Protein-Protein Interaction (PPI) Networks (STRING, IntAct, DIP, BioGRID), Functional and Pathway Enrichment (DAVID, Reactome, KEGG)

Wet Lab Techniques: Autoclave, UV/Vis Spectrometer, Centrifuge, Inverted Microscope, Colorimeter, Potentiometric pH meter, Multi-Mode Plate Reader, PCR, Gel Electrophoresis, UV Visualiser, Biochemical Test, Isolation, identification, and preservation of micro-organisms, MBRT test, Quality Analysis of water and food samples, Serial Dilution, Wine & Xanthan Gum Production, Protein Estimation, Carbohydrate Estimation, Quality Estimation of Amino Acids, Thin Layer Chromatography (TLC), Cell Viability, Staining Methods, Plant tissue sterilization and culture using different explants, Embryo & Anther Culture, Seed viability testing, Animal cell line maintenance, MTT Assay

Ongoing Research Work

  1. Mutational analysis of first-line drug receptors for MDR tuberculosis.
  2. Genomics and Multi-Omics Analysis of human cancer.

Courses and Certifications

  1. Gut Check: Exploring your microbiome, Coursera
  2. Computer-Aided Drug Design, Biotechnika
  3. Machine Learning for Beginners, Microsoft, Github
  4. Data Science Course – Mastering the Fundamentals, Scaler
  5. R for Beginners’, Daksh Foundation

Publications

  1. Extracellular Vesicular miRNA in Pancreatic Cancer: From Lab to Therapy, Cancers, MDPI. (Impact Factor = [hidden])
  2. Mechanistic influence of discreet conformation of human telomerase linker region, Journal of Biomolecular Structure and Dynamics, Taylor & Francis. (Impact Factor = [hidden])
  3. Structural variation and transitional analysis of embB receptor with its mutants leading to drug resistance in tuberculosis, Asian Journal of Microbiology, Biotechnology, & Environmental Sciences. (NAAS Rating = [hidden])
  4. CRISPR/Cas9 system in breast cancer therapy: advancement, limitations and future scope, Cancer Cell International, BMC. (Impact Factor = [hidden])
  5. Extracellular Vesicle-Based Therapy for COVID-19: Promises, Challenges and Future Prospects, Biomedicines, MDPI. (Impact Factor = [hidden])

Skills: Data Preparation, Experimentation, Uplift Testing, Analytics, Commercial Application, Gene Regulation, Network Analysis, Multi-Omics Data Integration, Machine Learning, Statistical Analysis, Protein Structure Prediction, Wet Lab Techniques

Cover Letter:

<[hidden]>

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *

×


Congratulations! You found the gift!