BOL: Related items

Search Shell Command History

Rahul Nayak — Thu, 12 Jun 2014 17:43:34 -0500

We use couple of hundreads of command in daily basis. Most of them are actually repeated several time. The question remain open how do I search old command history under bash shell and modify or reuse it?

Now a days almost all modern shell allows you to search command history if enabled by user. Use history command to display the history list with line numbers. Lines listed with with a * have been modified by user.

Shell history search command

Type history at a shell prompt:
$ history

It will display the list of all used commandline history with an serial number.

To search particular command, enter:
$ history | grep command-name
$ history | egrep -i 'scp|ssh|ftp'
Emacs Line-Edit Mode Command History Searching

To get previous command containing string, hit [CTRL]+[r] followed by search string:

(reverse-i-search):

To get previous command, hit [CTRL]+[p]. You can also use up arrow key.

CTRL-p

To get next command, hit [CTRL]+[n]. You can also use down arrow key.

CTRL-n

fc command

Apart from hostory command there are fc command to extract the command from history. The fc stands for either "find command" or "fix command.

For example list last 10 command, enter:
$ fc -l 10
To list commands 130 through 150, enter:
$ fc -l 130 150
To list all commands since the last command beginning with ssh, enter:
$ fc -l ssh
You can edit commands 1 through 5 using vi text editor, enter:
$ fc -e vi 1 5

Delete command history

The -c option causes the history list to be cleared by deleting all of the entries:
$ history -c

QuasR: Quantification and annotation of short reads in R

Neel — Fri, 13 Aug 2021 07:44:05 -0500

The QuasR package (short for Quantify and annotate short reads in R) integrates the functionality of several R packages (such as IRanges (Lawrence et al. 2013) and Rsamtools) and external software (e.g. bowtie, through the Rbowtie package, and HISAT2, through the Rhisat2 package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single R script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html

Bioinformatician’s Pocket Reference !!

RAJESH DETROJA — Sun, 08 Jun 2014 09:56:58 -0500

It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!

Address of the bookmark: http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/

Basics of BLAST Programs !

BioStar — Fri, 26 Jul 2024 06:04:26 -0500

The Basic Local Alignment Search Tool (BLAST) is a powerful bioinformatics program used to compare an input sequence (such as DNA, RNA, or protein sequences) against a database of sequences to find regions of similarity. Developed by the National Center for Biotechnology Information (NCBI), BLAST is widely used for identifying species, finding functional and evolutionary relationships between sequences, and predicting the function of novel sequences.

Key Features of BLAST:
1. Sequence Comparison: BLAST searches for local alignments between the query sequence and sequences in a database. It identifies regions of similarity, which can help infer functional and evolutionary relationships.

2. Speed and Efficiency: BLAST uses heuristic algorithms, making it faster than exhaustive search methods, suitable for large-scale database searches.

3. Versatility: There are several versions of BLAST for different types of sequence comparisons:
- blastn: Compares a nucleotide query sequence against a nucleotide sequence database.
- blastp: Compares a protein query sequence against a protein sequence database.
- blastx: Compares a nucleotide query sequence translated in all reading frames against a protein sequence database.
- tblastn: Compares a protein query sequence against a nucleotide sequence database translated in all reading frames.
- tblastx: Compares the six-frame translations of a nucleotide query sequence against the six-frame translations of a nucleotide sequence database.

4. Scoring and E-value: BLAST results are scored based on the quality and length of the alignments. The E-value (expect value) indicates the number of alignments one can expect to find by chance, with lower E-values representing more significant matches.

5. Output Formats: BLAST provides results in various formats, including plain text, HTML, XML, and JSON, making it adaptable for different types of analyses and integrations with other tools.

Applications of BLAST:
- Genomic Research: Identifying genes, understanding genetic diversity, and mapping genome sequences.
- Protein Function Prediction: Inferring the function of unknown proteins by comparing them to known protein sequences.
- Evolutionary Studies: Exploring evolutionary relationships between organisms by comparing their genetic material.
- Medical Research: Identifying pathogens, understanding disease mechanisms, and developing treatments by comparing sequences of interest.

Overall, BLAST is an essential tool in bioinformatics, offering a reliable and efficient way to analyze and interpret biological sequence data.

Assistant Professor in Medical Bioinformatics

Tue, 24 Jun 2014 01:46:36 -0500

Advt. No : ME-I/A-IV/03/14
No.of Posts:01 (SC)
Pay Scale:
Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.
Qualifications:
Area of Specialization:-
Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology
1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.
2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/
Immunology/Structural Biology etc
Experience:
1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical
Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.
2. Minimum two publication with atleast one in international journal and atleast one as first author
Desirable:-
Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)
Send your applications to O/O, Deputy Registrar, Recruitment & Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014
For more details,please visit website: http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf
Last Apply Date: 08 Jul 2014

TelomereHunter

Jit — Fri, 02 Feb 2018 04:23:59 -0600

TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.

TelomereHunter is available for download at the following address: https://pypi.python.org/pypi/telomerehunter/

Address of the bookmark: http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html

Postdoc position at Centre Méditerranéen de Médecine Moléculaire

Sun, 06 Jul 2014 11:23:06 -0500

The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).
The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ).

The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.

Candidates should hold a Ph.D. degree and have strong background in bioinformatics.
The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.
Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )

RAMI: a tool for identification and characterization of phylogenetic clusters in microbial communities

Jit — Mon, 07 Aug 2017 18:49:27 -0500

RAMI, which clusters related nodes in a phylogenetic tree based on the patristic distance. RAMI also produces indices of cluster properties and other indices used in population and community studies on-the-fly.

Availability: RAMI is licensed under GNU GPL and can be run or downloaded from http://www.acgt.se/online.html.

Address of the bookmark: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp051

Nuclear Dynamics Lab

Thu, 17 Jul 2014 15:03:27 -0500

Lab focus is to elucidate fundamental principles, new mechanisms, machineries and emergent properties that are involved in maintaining the genome and gene expression programmes for improvements in lifelong health and well-being for all.

More at http://www.babraham.ac.uk/our-research/nuclear-dynamics/

ACANA: An accurate and consistent alignment tool for DNA sequences

Jit — Wed, 06 Dec 2017 09:45:29 -0600

ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.

Address of the bookmark: https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm