More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

What Are lncRNAs?

lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.

Challenges in lncRNA Research

Identifying and understanding lncRNAs pose unique challenges:

1. High Sequence Variability: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.
2. Low Expression Levels: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.
3. Diverse Functions: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.

Bioinformatics: A Crucial Ally in lncRNA Research

Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here’s how:

1. Identification and Annotation

High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as StringTie, Cufflinks, and HISAT2 help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.

2. Functional Prediction

Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.

3. Network Construction

lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.

4. Epigenetic Studies

lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.

5. Clinical Applications

Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.

Case Study: lncRNAs in Cancer Research

lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.

Future Directions

The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:

• Integrative Analysis: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.
• CRISPR Screens: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.
• Therapeutic Development: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.

Conclusion

lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.

The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you’re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.

Lab Page http://gabi.cidbio.org/index/

• Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
• Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
• Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
• BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
• Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
• SeqAn – The modern C++ library for sequence analysis.

The symposium will focus on topics in the below mentioned areas.

Topics: Algorithms for biomolecular sequences / structures Bioinformatics databases and tools Protein function Structure based drug design Machine learning Deep learning Large scale data analysis Big Data NGS Analysis Protein interactions/network Molecular modelling/docking/screening Biomolecular structure and function More

Info: https://web.iitm.ac.in/bioinfo2/symposium2020/home

1. Make friends with local bioinformatics groups
2. Talk to your computing group
3. Obtain clear expectations
4. Rewrite your job description
5. Papers
6. Attend bioinformatics meetings
7. Try first, ask later

Address of the bookmark: http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/

Postdoc position (m/w/d)

in the field of computational evolutionary microbiology is available
for an initially limited period of 36 months at the earliest possible
date. The weekly working time corresponds to 100% of full employment
(If the legal requirements under collective bargaining law are met, the
tariff grouping is carried out up to pay scale 13 TV-L. The obligation
to teach amounts to 4 hours.

The Genomic Microbiology Group research interests are focused on
microbial genome evolution with an emphasis on the study of lateral gene
transfer. In our research we use both computational and experimental
approaches (see www.uni-kiel.de/genomik). The position offers the
opportunity to develop an independent research profile within the group
research focus. The successful applicant is expected to be involved
in teaching of bioinformatics and molecular evolution, including the
development of teaching materials (lectures/exercises/short videos).

Your profile:
· Doctoral or PhD degree in Molecular Evolution, Bioinformatics or
related fields.
· Knowledge and experience in programming (e.g., Python) and
biostatistical analysis (e.g., with R or MatLab).
· Any of the following expertise is an advantage: the analysis of
genomic or transcriptomic data, phylogenetic reconstruction,
comparative genomics.
· Good oral and written communication skills in English.
· Ability to teach in German is an advantage (alternatively, an
indication to do so from the 2nd year on).
· Skills and motivation to communicate and interact with other
scientists.

The Christian-Albrechts-University sees itself as a modern and
cosmopolitan employer. We welcome your application regardless of your age,
gender, cultural and social background, religion, ideology, disability
or sexual identity. We promote equality of the sexes.

The Christian-Albrechts-University is committed to the employment of
people with disabilities. Preference will be given to applications from
severely handicapped persons and persons of equal standing, provided
they are suitable.

We expressly welcome applications from people with a migration background.

For enquiries regarding the position, teaching obligations and research
topic please contact Prof. Tal Dagan: tdagan@ifam.uni-kiel.de.

Applications should be submitted by email to Mrs. Haacks
(dhaacks@ifam.uni-kiel.de) as a single PDF and include: (1) a letter of
motivation (max 1 page, Arial 11, line spacing 1.15), (2) CV, (3) PhD
certificate. Please use 'GMG postdoc application - [your name]'
as a subject.

Please, refrain from sending us application photos.

Application deadline: August 31 2021 or until the position is
filled. Interviews will take place during September/October 2021. The
planned starting date for the position is flexible (but in 2021).

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.

Address of the bookmark: https://github.com/AusARG/pipesnake

Webpage : https://www.scilifelab.se/about-us/
Opportunity: https://www.scilifelab.se/about-us/career/

Why Bioinformatics Matters More Than Ever

Every day, our world generates massive amounts of biological data—from genome sequences to microbiome profiles to real-time pathogen surveillance. Hidden within these datasets are the answers to some of the greatest challenges humanity faces: emerging diseases, antimicrobial resistance, environmental stress, genetic disorders, sustainable agriculture, and more.

Bioinformatics isn’t just a skill.
It’s the language of the future of biology.

By mastering it, you give yourself the power to:

Decode genomes and understand life at its most fundamental level

Identify patterns no microscope could ever reveal

Predict disease outbreaks before they occur

Accelerate drug discovery with computational precision

Contribute to open-source tools that empower scientists worldwide

You don’t just follow science—you drive it.

Every Expert Was Once a Beginner

Many newcomers feel intimidated. Command-line interfaces. R scripts. Python packages. Next-generation sequencing data. Complex machine learning models.

But here’s the truth: every bioinformatician started exactly where you are now—curious, unsure, but excited.

No one writes perfect code on day one.

No one understands genomics pipelines immediately.

What makes you a bioinformatician is not perfection, but perseverance.

When your script throws a cryptic error…
When your data refuses to format…
When your pipeline runs for 6 hours only to crash…

Remember: this is part of the journey.
Every error teaches you. Every retry strengthens you. Every breakthrough energizes you.

Bioinformatics Is Not Just a Career—It’s a Mindset

It’s the mindset of:

Problem-solving.

Continuous learning.

Turning chaos into clarity.

Seeing what others can’t.

Bioinformaticians are detectives of biological complexity. You sit at the intersection of innovation, using tools that can shape public health, medicine, agriculture, and ecology. Few fields give you such direct impact on the world.

Your Contribution Matters

As you work on your script, pipeline, genome, or model, remember:

Somewhere, your analysis might contribute to:

A new therapy

A faster diagnostic test

A better understanding of a pathogen

A more resilient crop

An open-source dataset that helps thousands

A discovery that rewrites textbooks

Your code may be small, but its ripple effect is powerful.

The Future Is Bioinformatics—And You Are Part of It

The world is shifting. Wet labs are integrating AI. Hospitals rely on genomic insights. Farmers use gene-level predictions. Governments monitor disease in real time. Students launch pipelines that become global tools.

This is a golden era—and you are not late.
You are exactly where you need to be.

Keep Pushing. Keep Learning. Keep Discovering.

Bioinformatics is a journey filled with challenges, but also with unmatched rewards.

So the next time you feel stuck, frustrated, or overwhelmed, remember:
You’re building the science of tomorrow.

Be proud. Stay curious. Keep going.
Your work matters more than you think.