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4 published- 6/11/2026
مجال biotechnology و molecular biology و bioinformatics المجالات دي في مصر مطلوبه في سوق العمل و لا اكاديميا فقط و تنصح حضرتك بدخولها لو لسه طالب و لا يتجه ناحيه الميكرو او كيميا برغم من حب مجالات البايو اكتر
هى التخصصات دى موجودة بس فرصها قليلة فى مصر , فلو عايزها ادخل فيها بس حضر نفسك لسفر برا منحة دراسية علشان تتطلع تكمل وتلاقى فرص اكتر برا لكن لو عايز شغل اكتر شوف المصانع عايزة ايه سواء بقى كمياء او ميكرو فى معامل اغذئية او ادواية فى شركات
Read answer → - .6/11/2026· asked by رويدا محمد
لو مهتمه جدا بمرض الزهايمر وطريقه التشخيص المبكر ليه او كيفيه التطوير والبحث عن علاج ليه وعايزه استخدم البايوانفورماتكس كاداه تساعدني بس لسه ما بداتش لان سنه تانيه ايه هي الطريقه الصحيحه نبتدي في المجال ده صح بدون ما يتضحك عليا من اعلانات الكورسات
لزم الاول تبدا تقرا فى مجالات ال molecular neuroscience وتحددى ايه افضل تخصص ليكى فيه زى مثلا Neurotranscripomes وبعد التعلم هتكونى محتاجة تتعلمى Machine & Deep Learning علشان خطوة ال predication & diagnosis
Read answer → - 6/11/2026
Is learning coding and programming languages for bioinformatics analysis is a must? or I can familiarize myself with it through various types of analysis? Because it frustrates me expecially because i had less than 1 yr trying to learn R which was in vain
Yes, programming and statistics are the backbone of almost every field in bioinformatics. Strong skills in these areas will make it much easier to learn genomics, transcriptomics, epigenomics, single-cell analysis, machine learning, and other advanced topics. You can start learning step by step through YouTube playlists and free online resources. There are many excellent courses available in R programming, ranging from beginner to advanced levels. Explore different courses, compare teaching styles, and choose the one that best matches your learning preferences and goals. If free resources are not enough or you need a more structured learning experience, consider enrolling in a specialized paid course. Focus on courses that combine R programming with a specific bioinformatics domain, such as: * R Programming for Bioinformatics * R for Transcriptomics Analysis * R for Genomics and Comparative Genomics * R for Single-Cell RNA-Seq Analysis * R for Epigenomics * R for Metagenomics * R for Machine Learning in Bioinformatics The most important thing is not just learning the syntax of R, but applying it to real biological datasets and projects. Building hands-on experience through practical analyses will help you develop the skills that research groups and PhD programs are looking for.
Read answer → - RNAseq6/11/2026· asked by Soliman
have an M.Sc. in Genetics and Molecular Biology and experience in RNA-seq and bioinformatics. What skills should I focus on to become competitive for international PhD positions in computational genomics?
Good question. My advice is to move beyond RNA-seq and expand your expertise into broader genomics and more advanced analytical approaches. Start by strengthening your knowledge of comparative genomics, population genomics, structural variation analysis, and pan-genomics. These areas provide a strong foundation for modern computational genomics research. Next, move into epigenomics, including DNA methylation, histone modifications, chromatin accessibility, and regulatory genomics. Once you are comfortable with bulk epigenomic data, advance to single-cell technologies such as Single-cell ATAC-seq (scATAC-seq), Single-cell Methylation Sequencing, and multi-omics integration approaches. After building a solid genomics and epigenomics background, focus on integrating Machine Learning (ML) and Deep Learning (DL) into biological data analysis. Developing skills in predictive modeling, representation learning, and AI applications for genomics will significantly increase your competitiveness for international PhD programs and scholarships. At the same time, work on publishing research papers across different areas of bioinformatics and genomics. A strong publication record, combined with expertise in advanced genomics, single-cell technologies, and AI-driven analysis, will help you stand out among applicants and demonstrate your readiness for cutting-edge computational genomics research.
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