Research in Bioinformatics

Latest Advancements in the field of Bioinformatics 2023

The field of bioinformatics has witnessed significant advancements in 2023, paving the way for transformative applications in biological research, medicine, and healthcare.  Some of the key developments include: AI in Drug Discovery: Artificial Intelligence (AI) and machine learning (ML) are revolutionizing drug discovery by accelerating the prediction of molecular interactions and the identification of potential […]

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Bioinformatics tools and databases for analysis of next-generation sequence data in oncology

In the world of cancer research, bioinformatics tools and databases are like super-powered detectives, helping scientists make sense of complex genetic data. Let’s explore some key tools that are making a big impact: TCGA: Your Genomic Encyclopedia Imagine a massive library containing genetic information from over 11,000 cancer patients. That’s TCGA! It’s a goldmine for

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Exploring Transcriptomics Techniques and Applications

Introdution to RNA-Seq and its application in plant science

RNA-Seq, employing high-throughput sequencing, is pivotal for studying RNA expression in plant science, offering insights into the transcriptome’s identity, quantity, and structure, along with molecular interactions and modifications¹. Applications in Plane Science: Transcriptome Assembly: Facilitates assembly in plant species with complex genomes or lacking a reference genome. Identifies novel genes, isoforms, alternative splicing events, and

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Exploring Transcriptomics Techniques and Applications

Exploring Transcriptomics: Techniques and Applications

Transcriptomics, the study of the complete set of RNA transcripts within a cell, tissue, or organism, is a pivotal field that provides invaluable insights into gene expression, regulation, and function. In this blog post, we will delve into some of the primary transcriptomics techniques, shedding light on their applications and contributions to various biological contexts.

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Role of transcriptomics in infectious diseases

Infectious diseases are caused by microorganisms such as viruses, bacteria, fungi, and parasites that invade and multiply in the host organism. They are a major threat to human health and well-being, especially in developing countries where they account for a large proportion of morbidity and mortality. Infectious diseases are also constantly evolving and adapting to

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Multiple Sequence Alignment Technique

Multiple sequence alignment (MSA) is a technique used in bioinformatics to compare and analyse the similarities and differences between three or more biological sequences. The sequences can be DNA, RNA, or protein sequences. MSA is an essential tool for studying the evolutionary relationships between different species and identifying conserved regions in the sequences. Why is

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Tools and Databases for Analysis of Next Generation Sequencing in Bioinformatics

Next-generation sequencing (NGS) technologies have revolutionized the field of genomics, enabling the rapid and cost-effective generation of massive amounts of data. However, the analysis and interpretation of NGS data poses significant challenges, requiring specialized bioinformatics tools and databases. In this blog post, we will review some of the common tasks and applications of NGS data

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How bioinformatics can help track the origin and evolution of the Christmas tree

Christmas trees are a popular and festive tradition that many people around the world enjoy every year. But have you ever wondered where they came from and how they evolved over time? In this blog, we will explore how bioinformatics, the application of computational tools and methods to biological data, can help us answer these

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QSAR and ML: A Powerful Combination for Drug Discovery

Quantitative structure-activity relationship (QSAR) is a method that uses mathematical models to predict the biological activity or physicochemical property of a molecule based on its structure. QSAR has been widely used in drug discovery, environmental toxicology, and chemical risk assessment for decades. However, traditional QSAR models often suffer from limitations such as low accuracy, poor

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