https://fold.it/portal/

Address of the bookmark: https://fold.it/

So, What Is Data Science?
At its core, data science is the interdisciplinary field that extracts knowledge and insights from data using programming, statistics, and domain expertise. In bioinformatics, data science enables us to turn gigabytes of sequence data into biological meaning.

Imagine trying to understand gene regulation in cancer by analyzing thousands of RNA-seq samples, or predicting antibiotic resistance from bacterial genomes—these challenges are not solvable through wet lab experiments alone. They require data-driven thinking.

Data Science Meets Bioinformatics
Bioinformatics is inherently a data science domain. From genomics to systems biology, every field in modern biology relies on data science techniques to:

Clean and process massive datasets

Discover patterns in high-dimensional data

Build predictive models (e.g., for disease classification)

Visualize complex biological networks and trends

Integrate diverse data types (e.g., transcriptomic + epigenomic data)

The Bioinformatics Toolkit
Here’s what data science typically looks like in bioinformatics:

Task Data Science Role
Sequence alignment Efficient algorithms, indexing, parallel processing
Gene expression analysis Statistical modeling (e.g., DESeq2, limma)
Variant calling Data filtering, probabilistic models
Clustering of cells in single-cell data Unsupervised learning
Protein structure prediction Deep learning models (e.g., AlphaFold)
Metagenomics Data integration, classification, dimensionality reduction

Common tools include Python, R, Bioconductor, scikit-learn, Pandas, Seurat, and TensorFlow—often working together in reproducible workflows.

It's Not Just About Coding
A common misconception is that bioinformatics is just programming or scripting. But being a data scientist in bioinformatics also means:

Understanding experimental design

Asking biologically meaningful questions

Choosing the right statistical or machine learning models

Communicating findings effectively (e.g., plots, dashboards, papers)

In other words, data science in bioinformatics is where biology, statistics, and computer science converge.

Why It Matters
The real power of data science in bioinformatics is its ability to scale discovery.

Instead of studying one gene, we can study thousands.

Instead of analyzing one species, we can explore entire ecosystems.

Instead of waiting months for lab results, we can generate hypotheses in days.

From personalized medicine and cancer diagnostics to agricultural genomics and pandemic surveillance, data science is at the heart of the bioinformatics revolution.

Final Thoughts
If you’re a biologist who’s curious about code, or a data enthusiast fascinated by life sciences, bioinformatics is your playground—and data science is your toolkit.

In bioinformatics, data science isn’t just useful. It’s essential.

Address of the bookmark: http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html

More at https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa179/5804978?rss=1

Address of the bookmark: https://github.com/CMU-SAFARI/Apollo

Address of the bookmark: https://www.nature.com/articles/s41588-020-0700-8

More at http://www.nipgr.res.in/careers/vacancies_latest.php#

A qualified candidate should hold a Ph.D. in a relevant field including
Agronomy, Statistics, Bioinformatics, Plant Breeding, Plant Genetics or
Quantitative Genetics. For the position in Biometry and Bioinformatics, the
applicants capable of teaching fundamental statistics/bioinformatics
courses or with experience in crop science are preferable; for Plant
Breeding and Genetics, the applicants capable of teaching fundamental plant
breeding courses, with experience in crop breeding, or training in
quantitative genetics are preferred.

The application package should include two letters of reference and five
printed copies of the following documents (1) curriculum vitae, (2)
publication list, (3) undergraduate and graduate transcripts if applying
for the Assistant Professorship, (4) a photocopy of the Ph.D. diploma, (5)
teaching plan and course outline or syllabus (6) research proposal, (7) a
cover letter indicating the rank to apply, and one representative original
research article which was published by the applicant being the 1st or
corresponding author in an SCI peer-reviewed journal within 5 years (after
August 1, 2016); a copy of doctoral dissertation can be the representative
article if applying for the Assistant Professorship; (8) reprints of the
selected publications published within 7 years (after August 1, 2014).

The application package should mail to the Chair, Dr. Li-yu Daisy Liu
(lyliu@ntu.edu.tw), in the Department of Agronomy, National Taiwan
University, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan, before
December 15, 2020 for full consideration.

The winners will have their essays published by Science, win up to USD 30,000 and be invited to Sweden to attend the award ceremony. Get ready for a life-changing moment in your scientific career. 

Application deadline: July 15th, 2019

Eligible entrants must have been awarded their doctoral degree in 2017 or 2018. The winners from each category will compete for the Grand Prize. 

Read more: scienceprize.scilifelab.se
Questions/Inquiries: SciLifeLabPrize@aaas.org

Interested in taking a six month break from the research/academic track to work in a different part of the world and share your expertise where it is needed? Science-Corps has launched a new fellowship, which provides STEM PhD graduates the opportunity to teach science, design curriculum, and build scientific capacity abroad.

Science-Corps is recruiting STEM PhD students near degree completion and up to four years post completion for placement starting June of 2018.

Applications are due by January 31, 2018.

If interested, visit http://www.science-corps.org/

“The useful features of NgAgo for genome editing include the following.First, it has a low tolerance to guide–target mismatch. A single nucleotide mismatch at each position of the gDNA impaired the cleavage efficiency of NgAgo, and mismatches at three positions completely blocked cleavage in our experiments. Second, 5′ phosphorylated short ssDNAs are rare in mammalian cells, which minimizes the possibility of cellular oligonucleotides misguiding NgAgo.Third, NgAgo follows a ‘one-guide-faithful’ rule, that is, a guide can only be loaded when NgAgo protein is in the process of expression, and, once loaded, NgAgo cannot swap its gDNA with other free ssDNA at 37 °C. All of these features could minimize off-target effects. Finally, it is easy to design and synthesize ssDNAs and to adjust their concentration, which is difficult with the Cas9-sgRNA system, if the sgRNA is expressed from a plasmid and the normal dosage of an ssDNA guide is only ~1/10 of that of a sgRNA expression plasmid.

NgAgo might be a more orderly way and perhaps even simpler way to go about genome editing than CRISPR, but the jury is still out on that until there are more papers and data. The NgAgo edit efficiency at this preliminary stage of technology development seems very strong. See the pics below

Reference: http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3547.html