This month, we’re excited to showcase new opportunities for learners, researchers, and professionals looking to advance their skills in next-generation sequencing and omics data analysis. From hands-on training in Next-Generation Sequencing (NGS), Clinical Trials Analytics, Proteomics, R Programming, and Molecular Modeling & Simulations, to celebrating outstanding student research achievements, this newsletter highlights the latest developments across our learning community.
We’ll cover key topics including:
Introduction to Next-Generation Sequencing and Omics Technologies
Next-Generation Sequencing Workflow & Sample Preparation Essentials
Library Preparation Techniques for DNA & RNA
Hands-On Whole Exome Sequencing Data Analysis
ACMG Guidelines Everview; Variant Prioritization Strategies
🔗 Register to access the complete curriculum and receive assistance from our team: https://forms.gle/SMexf9AGnvbNAGpy8
We’ll cover key topics including:
AI in Clinical Trials and where ML is used in Pharma, CRO & Biotech
Structured, Unstructured, and Operational Clinical Trial Data Overview
Data Wrangling, Exploratory Data Analysis, & Feature Engineering
Building a Patient Dropout Prediction Model using scikit-learn
Role of Natural Language Processing in Automating Safety Review
Transformer-based models: BERT, ClinicalBERT & BioBERT
🔗 Register to access the complete curriculum and receive assistance from our team: https://forms.gle/kPhv2e6buqdb5eD17
We’ll cover key topics including:
Mass Spectrometry-Based Proteomics: Principles and Innovations
Proteomics Data Processing and Visualization (Heatmaps, Volcano Plots, PCA)
Protein-Protein Interaction Networks and Systems Analysis (Cytoscape, STRING)
Machine Learning and Feature Selection in Proteomics
Cancer Immunotherapy | Immunotherapeutic Targets Using Proteomics
Hands-On Interpretation of LC-MS/MS Proteomics Data
🔗 Register to access the complete curriculum and receive assistance from our team: https://forms.gle/dptrxdTm1J5G5WUN8
We’ll cover key topics including:
Introduction to R coding for omics data analysis (R, RStudio, Google Colab)
Data import and preprocessing techniques (Base R, tidyverse)
Creating and customizing visualizations (ggplot2)
Performing statistical tests like t-tests and ANOVA
Bioconductor packages for gene expression analysis (limma, DESeq2)
Conducting pathway and enrichment analysis (clusterProfiler)
🔗 Register to access the complete curriculum and receive assistance from our team: https://forms.gle/kARjd4o5g71T3ZrL7
We’ll cover key topics including:
Introduction: Molecular Modeling, Molecular Dynamics Simulations Fundamentals
Sequence to Structure: Protein Structure Prediction and Preparation
Ligand Preparation and Molecular Docking
Analyzing Simulation Trajectories and Refinement
Advanced Topics and Current Trends in Modeling & Dynamics
🔗 Register to access the complete curriculum and receive assistance from our team: https://forms.gle/9tMuFo5TwJS3tftQ6
We are thrilled to celebrate Maria Ajmal, a dedicated participant in our OmicsLogic Bioinformatics & Data Science Research Program, on the successful publication of her preprint on bioRxiv! 📄🔬
Her project explores how the Influenza A virus (H3N2) may encode miRNA-like molecules that regulate human host genes involved in antiviral defense and immune signaling. The work highlights potential molecular interactions that may contribute to influenza pathogenesis and provides candidates for future experimental validation.
Publication Link: https://www.biorxiv.org/content/10.64898/2026.05.18.725090v1
Huge congratulations to Priyambada and Dr. Kelvin on successfully completing their research projects as part of the OmicsLogic Biomedical Data Science Research Program!
Priyambada’s project, “Understanding the Molecular Landscape of Relapsing-Remitting Multiple Sclerosis,” explored gene expression changes and disrupted biological pathways in RRMS patients to uncover molecular mechanisms underlying disease progression and immune dysfunction.
Dr. Kelvin’s project, “Integrated Multi-Omics Analysis of TCGA Lower-Grade Glioma”, investigated the molecular and transcriptional landscape of lower-grade glioma to identify key driver mutations, dysregulated pathways, and potential biomarkers associated with tumor progression and immune dysfunction.
Excited to embark on a research journey like this?
🔗 Register to receive more information and assistance from our team: https://forms.gle/M7sYiieowMdaz9ie7
For queries, contact us at communication@omicslogic.com / support@omicslogic.com.
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