1. SPAdes: An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.

2. ABySS: A parallelized assembler for large genomes that uses de Bruijn graphs.

3. Velvet: Another de Bruijn graph-based assembler optimized for short-read sequencing data.

4. SOAPdenovo: A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.

5. MaSuRCA: A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.

6. Canu: A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.

7. Flye: A long-read assembler suitable for bacterial and small eukaryotic genomes.

8. SMARTdenovo: An assembler designed for long reads, particularly suited for PacBio data.

9. SPAdes Long Read (SPAdesLR): An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.

10. Minia: An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.

11. Unicycler: A hybrid assembler that combines short and long reads for circular bacterial genome assembly.

12. wtdbg2: A de Bruijn graph assembler for long reads, efficient for very large genomes.

13. Shasta: A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.

14. Sparc: An assembler designed to handle noisy long reads from Nanopore sequencing.

15. CANA: An assembler for metagenomic data, particularly for complex and diverse microbial communities.

16. Ra Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.

Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

Research Area:
Analysis of Next Generation sequence data in cancer
Methods for analysis of structural variation in cancer genomes
Next Generation sequencing in malaria
Computational comparative genomics
Sensitive genomic sequence search techniques using hidden Markov models
Tasmanian devil facial tumour disease

Link @ http://www.wehi.edu.au/faculty_members/dr_tony_papenfuss

The US born Sangeeta Bhatia at Massachusetts Institute of Technology (MIT) has developed a cheap, simple, paper test that can detect cancer. These diagnostic, which works much like a pregnancy test, could reveal within minutes, based on a urine sample, whether a person have cancer or not. The MIT media announce the major and amazing breakthrough in cancer diagonistics. These newly developed technology will allow non-communicable diseases to be detect at early stage, which will be cheap and easily accessible to the masses. For the developing world it would be exciting to adapt it instead to a paper test that could be performed on unprocessed samples in a rural setting, without the need for any specialized equipment. The simple readout could even be transmitted to a remote caregiver by a picture on a mobile phone.

The MIT professor and Howard Hughes Medical Institute investigator Sangeeta Bhatia, who is also the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, invented a new class of synthetic biomarker, which is highly specialized instrument to do these kind of analysis. These paper test essentially relies on nanoparticles that interact with tumor proteins called proteases, each of which can trigger release of hundreds of biomarkers that are then easily detectable in a patient's urine. The MIT nanoparticles are coated with peptides (short protein fragments) targeted by different MMPs. These particles congregate at tumor sites, where MMPs cleave hundreds of peptides, which accumulate in the kidneys and are excreted in the urine.

To create the test strips, the researchers first coated nitrocellulose paper with antibodies that can capture the peptides. Once the peptides are captured, they flow along the strip and are exposed to several invisible test lines made of other antibodies specific to different tags attached to the peptides. If one of these lines becomes visible, it means the target peptide is present in the sample. The technology can also easily be modified to detect multiple types of peptides released by different types or stages of disease.

In tests in mice, the researchers were able to accurately identify colon tumors, as well as blood clots. Bhatia says these tests represent the first step toward a diagnostic device that could someday be useful in human patients. "This is a new idea — to create an excreted biomarker instead of relying on what the body gives you," she says. "To prove this approach is really going to be a useful diagnostic, the next step is to test it in patient populations."

Reference:

Image: jasongrowclients

Homepage: http://lmrt.mit.edu/about.html

http://web.mit.edu/newsoffice/2014/a-paper-diagnostic-for-cancer-0224.html

http://timesofindia.indiatimes.com/home/science/PIO-develops-cheap-paper-test-to-detect-cancer/articleshow/30963615.cms

C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039

Address of the bookmark: https://depmap.sanger.ac.uk/

http://www.sidowlab.org/