Now, two research groups have engineered new optogenetic proteins that can be used to efficiently silence neurons. One of the two new proteins comes from the lab of Karl Deisseroth, a psychiatrist and neuroscientist at Stanford University who helped develop optogenetics as a research tool. His group’s new “off” switch for neurons was created by changing 10 of the 333 amino acids in an existing optogenetic protein, which itself had been engineered by combining natural proteins from green algae. That advance “creates a powerful tool that allows neuroscientists to apply a brake in any specific circuit with millisecond precision,” said Thomas Insel, director of the National Institute of Mental Health, in a released statement. The other new silencing protein, developed by scientists at the Humboldt University of Berlin and collaborators, was created by changing amino acids in the same existing optogenetic protein. 

Some researchers are also looking to optogenetics as a potential treatment for patients with a variety of conditions (see “For Mice, and Maybe Men, Pain Is Gone in a Flash,” and “Flipping on the Lights to Halt Seizures”) but there are huge challenges to overcome. The method requires genetic modification of cells to make them light-sensitive. It also requires implanted light sources for all but the shallowest of nerve endings.

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

More @ http://news.yale.edu/2013/10/17/researchers-rewrite-entire-genome-and-add-healthy-twist

News Reference: Yale news

Image Source: Sciencedaily.

Evolution provides the overarching framework for organizing our understanding of biological phenomena at multiple structural levels and spatio-temporal scales. As such, evolutionary biology is more of a perspective or weltanschauung on the living world rather than a sub-discipline of biology. Unfortunately, despite the centrality of evolution to all thinking in biology, evolutionary biology remains neglected in the Indian context although research in many areas, not traditionally thought to be within the ambit of evolutionary biology, would greatly benefit from an evolutionary perspective.

The first school in evolutionary biology in the country, sponsored by SERB, will be conducted at the Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru. The school aims to provide participants with an introduction to the historical development of evolutionary thought and the various ecological, genetic and developmental aspects of the evolutionary process. The school will also provide an introduction to formal evolutionary theory and statistical methods for the analysis of evolutionary data.

Master’s/Ph.D. scholars, postdoctoral researchers and young faculty members in India may apply online on or before 31 December 2018 at http://school2019.serbevolschool.in, where additional details about the school can also be found. In case of any difficulty with the submission of applications, please e-mail Prof. T. N. C. Vidya, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bengaluru, at tncvidya.lab@gmail.com.

Selected participants will be provided 3-tier AC train fare and local hospitality. There is no registration fee.

Application closing date 16/09/2024

Details of the post and application process can be found at the following
url:

https://vacancies.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=202575WW5Z&WVID=9918109NEm&LANG=USA

Informal enquiries may be made by email to the Head of the School of
Life Sciences Prof Terence McGenity at tjmcgen@essex.ac.uk(all formal
applications for the post should be made online through the University
of Essex website).

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

The Biotite package bundles popular tasks in computational biology into an unifying framework, which is easy to use on the one hand side, but is also computationally efficient due to intensive usage of NumPy and Cython. This package focuses on working with sequence and structure data and supports various file formats and analysis and manipulation functions.

Address of the bookmark: https://github.com/biotite-dev/biotite