Sakshi Dhiman – Unlocking the Secrets of Life: A Journey Through AI, Bioinformatics, and Drug Discovery

CURRICULUM VITAE

Sakshi Dhiman

SUMMARY:

Biotechnology postgraduate with expertise in bioinformatics, molecular docking, and AI/ML applications in biology for computational analysis and drug discovery.

EXPERIENCE:

Training Program in AI and ML in Biology, Bioinformatics and Computational Biology – Online | Biotecnika | September 2024 – October 2024

• Successfully completed 30 days hands-on training in AI, ML applications in biology, bioinformatics and computational biology
• Learned and implemented machine learning algorithms for biological data analysis – Supervised, Unsupervised and Reinforcement
• Applied deep learning models (CNNs, RNNs) for genomics and proteomics data analysis – DeepSEA Chromatin, HumanBase ExPecto, AlphaFold
• Conducted data clearing techniques for biological data to enhance model accuracy
• Implemented deep learning for drug discovery and multi-omics

Bioinformatics Summer Training + Internship – Online | Biotecnika | June 2024 – July 2024

• Conducted genomics and sequencing analyses – NGS, DNA/RNA sequencing, and miRNA profiling
• Worked with bioinformatics databases – UCSC Genome Browser, Ensembl, KEGG, STRING, and ClinVar for data retrieval and analysis
• Performed molecular docking and drug discovery studies – AutoDock, PatchDock, ClusPro, and QSAR modeling
• Analyzed ADMET and pharmacokinetics – SwissADME, BOILED-Egg Model, and metabolic and Biochemical pathway analysis
• Gained expertise in protein structure modeling with PDB, Swiss-ExPASy, I-TASSER, and Phyre2
• Conducted phylogenetic and sequence analysis – ClustalW, Clustal Omega, NCBI, and DDBJ
• Applied computational biology techniques in functional genomics, microbiome studies, and MicrobiomeDB
• Familiarized with publication and research tools – Elsevier, Springer, Wiley, MDPI, and Bentham Science

Industrial Molecular Docking Practical online Workshop by Quantumzyme – Online | Biotecnika | October 2023

• Hands-on training in AutoDock, AutoDock Vina, PyRx, Discovery Studio, PyMOL, and Chimera
• Conducted ligand-receptor preparation, docking simulations, and result analysis
• Worked on a real-time molecular docking project with report submission

TECHNICAL SKILLS:

• Bioinformatics (BLAST, sequence analysis)
• Molecular docking (AutoDock, AutoDock Vina, PyRx, ADMET)
• AI/ML in biology (Python / R, data preprocessing)
• Data Analysis (Statistics, Matplotlib, Seaborn, ggplot)

EDUCATION:

• Dual Degree – [hidden] (Hons) Biotechnology – [hidden] (Hons) Biotechnology | September 2022 – September 2024

CERTIFICATIONS:

• AI/ML in biology, bioinformatics and computational biology | 82% scored | 15 October 2024
• Bioinformatics summer training+internship | 95% scored | 30 July 2024
• Industrial molecular docking practical online workshop by Quantumzyme | 16 October 2023

Skills:

Bioinformatics, Molecular Docking, AI/ML, Data Analysis, Genomics, Proteomics, Drug Discovery, Computational Biology

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Cover Letter:

Dear Hiring Manager,

I am excited to apply for the AI/ML Analyst position. With a strong background in biotechnology and a passion for AI and machine learning, I specialize in applying computational techniques to biological data analysis and drug discovery.

I have completed training in:

AI in Biology & Bioinformatics

Bioinformatics Summer Training

Industrial Molecular Docking

My expertise includes machine learning algorithms, bioinformatics tools, and predictive modeling for biological research. I am eager to bring my analytical skills and AI-driven approach to your team and would love the opportunity to discuss how I can contribute.

Sincerely,
Sakshi Dhiman