Primer design, Sequence Analysis, Statistical and computing methods, Omics and proteomics, Signal processing and protein database. NCBI BLAST, Mega X, CLUSTAL W softwares
If you wish to design/write a lab manual for agricultural bioinformatics then you should first do your homework and make yourself familiar with the topic and then ask specific questions.
Sanjay Nagar Sanjay, Sabine Strehl gave you very good advice. Look at the current ideas and manuals and research the field to know what ideas are established vs what information is harder to obtain. Do a search in Google and Google Scholar to see what’s being published and how the ideas are presented. - Insure you are able to offer a clear & understandable way to apply technology to transform information into ideas people can use. Emphasis on “understand and use”. —- Implied in the latter; you're a good writer and equally good at describing complex and relatively new techniques in a manner that people can understand. —- Below are links that show some current publications…….
Designing a Bioinformatics in Agriculture lab manual involves a combination of theoretical concepts, practical experiments, and computational analysis. Here are some useful insights and general experiments that can be included in the lab manual:
Introduction to Bioinformatics in Agriculture: Provide an overview of the field of bioinformatics and its applications in agriculture, including crop improvement, genetic analysis, and plant genomics.
Sequence Retrieval and Database Search: Teach students how to retrieve DNA or protein sequences from public databases such as NCBI, UniProt, or specialized plant genomics databases. Guide them in performing sequence similarity searches using tools like BLAST.
Multiple Sequence Alignment: Introduce students to multiple sequence alignment techniques using tools like ClustalW or MUSCLE. Allow them to align and analyze DNA or protein sequences from different crop species or gene families.
Phylogenetic Analysis: Teach students how to construct phylogenetic trees using software such as MEGA or PhyML. Guide them in inferring evolutionary relationships among different crop species or varieties based on sequence data.
Functional Annotation: Introduce students to functional annotation tools such as InterProScan or Blast2GO. Show them how to assign putative functions to unknown or novel sequences based on similarity to annotated proteins.
Gene Expression Analysis: Provide an overview of gene expression analysis using tools like GEO or ArrayExpress. Guide students in accessing and analyzing gene expression data for agriculturally important crops under different conditions or treatments.
SNP Analysis: Teach students how to analyze single nucleotide polymorphisms (SNPs) using tools like PLINK or TASSEL. Show them how to perform association studies, genetic diversity analysis, or marker-trait association analysis in crops.
Genome Visualization: Introduce students to genome visualization tools like IGV or JBrowse. Guide them in exploring annotated genomes, gene models, and genomic features of agriculturally important crops.
Protein Structure Prediction: Demonstrate protein structure prediction tools such as SWISS-MODEL or I-TASSER. Show students how to predict and analyze protein structures relevant to agriculture, such as enzymes or receptor proteins.
Data Integration and Visualization: Teach students how to integrate and visualize various types of biological data using tools like Cytoscape or R/Bioconductor. Guide them in constructing biological networks or visualizing omics data.
These experiments can provide students with hands-on experience in applying bioinformatics techniques and tools to address agricultural research questions. It's important to provide clear instructions, step-by-step protocols, and sample datasets for students to work with. Additionally, encourage students to analyze and interpret their results, fostering critical thinking and scientific inquiry skills.
Sanjay Nagar Mohammad Shahbaz Khan Sabine Strehl Sanjay, with the addition of Mohammad's suggestions it looks to me that you now have information to make the best manual ever. - Add my "thank you" to Mohammed & Sabine.