🧵#Bioinformatics applications, a THREAD🧵🧵:
One of the key areas of #bioinformatics is the application of #computational techniques to the analysis of large #datasets of biological information, such as #genomic, #proteomic, and #metabolomic data.
#Genomic data provides information about the entire genetic makeup of a #biological system, including the #sequences of all its genes and the #regulation of their e#xpression.
#Proteomic data provides information about all the #proteins in a biological system, including their #structures, functions, and interactions.
#Metabolomic data provides information about the small #molecules involved in the #metabolism of a biological system, including intermediates, products, and waste products.
By analyzing these datasets, #bioinformaticians are able to gain new insights into the workings of living systems, and to develop new technologies and therapies to improve human health and well-being.
#Bioinformatics has many exciting applications in areas such as #drug discovery, #personalized #medicine, agricultural biotechnology, and environmental biotechnology.
Join us as we explore the world of bioinformatics and see how it is helping to unlock the secrets of the natural world and improve human health and well-being. We're cloud genomics.

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More from @CloudGenomics

Dec 5
Are you interested in getting started in #bioinformatics but not sure where to begin? Here are some tips to help you get started on your journey. A THREAD🧵🧵:
Start by learning a high-level #programming language, such as #Python or #R, and familiarizing yourself with data structures and #algorithms commonly used in #bioinformatics. The #BioPython and #Bioconductor libraries are great resources for this.
Next, learn about #genomic data formats and standards, such as #FASTA, #FASTQ, and #GFF. This will allow you to effectively manipulate and analyze large-scale #genomic #datasets. The #NCBI SRA and #EBI ENA databases are great places to find real-world data to work with.
Read 12 tweets
Dec 3
Thread explaining a complete pipeline for #RNA-seq analysis 🧵
RNA-seq is a powerful technique that allows researchers to study the expression of genes at a global level. The RNA-seq analysis pipeline typically involves several different steps, including:
1. Quality control and filtering of the raw RNA-seq data
2. Alignment of the reads to the reference genome
3. Assembly of the aligned reads into transcripts
4. Quantification of gene and transcript expression levels
Read 8 tweets
Dec 2
🧬🧵here is a Twitter thread explaining #Bioinformatics in simple terms:🧬🧵
#Bioinformatics is the field that uses computational tools and methods to analyze and interpret #biological #data.
This can include analyzing #DNA and #protein #sequences, predicting the structure and function of #molecules, and modeling biological systems.
Read 7 tweets

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