BOL: Related items

Supposedly Educational R

Rahul Nayak — Tue, 03 May 2016 16:43:08 -0500

R 3.3.0 (codename “Supposedly Educational”) was released today. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code in Rgui:

install.packages("installr") # install 
setInternet2(TRUE)
installr::updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.). There is also a step by step tutorial (with screenshots) on how to upgrade R on Windows, using the installr package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to open an issue in the github page.

Lawley Lab

Mon, 09 May 2016 03:29:51 -0500

Lawley Lab are covered with a complex microbial community, known as our microbiota, which plays important roles in our physiology, immunity, metabolism and sustenance. Within the human gastrointestinal tract alone there are over 1,000 bacterial species, which amounts to approximately 10 times more cells than we harbor in our entire body and 200 times more genes than are found within our genome. Lawley Lab are really a 'supraorganism' consisting of our 'human' and 'microbial' selves.

More at http://www.sanger.ac.uk/science/groups/lawley-lab

Navin Lab

Wed, 18 May 2016 16:40:14 -0500

NAvin laboratory has pioneered the development of single cell sequencing technologies. They apply these tools to study complex biological processes that occur in human cancers including tumor initation, clonal evolution, invasion, metastasis and chemoresistance. These processes have previously been difficult to study with genomic technologies using bulk tissues

More at http://www.navinlab.com/navinlab/home.html

RA at UNIVERSITY OF HYDERABAD

Sun, 29 May 2016 11:50:37 -0500

UNIVERSITY OF HYDERABAD

School of Life Sciences

Department of Animal Biology

Applications are invited on a plane paper (along with copies of educational qualifications and experience) from eligible candidates for the selection of following position to work under a collaborative research project entitled “Development and application of high resolution genome conformation capture technology to investigate genome architecture in space and time” between University of Hyderabad and CR Rao advanced Institute of Mathematics, Statistics and Computer Sciences, sponsored by Department of Biotechnology, Government of India, New Delhi

Name and No. of positions JRF‐ONE

Emoluments for the position Rs. 25,000/p.m. + Eligible HRA

Qualifications MSc or M.Tech in any branch of biology/bioinformatics/computational biology/computer sciences/Mathematics/Physics

Duration Appointments are made initially for ONE year and can be extended further TWO years or until the duration of project

Our laboratory is interested in understanding signalling and spatiotemporal dynamics of 3‐Dimensional genome architecture and gene expression during embryonic stem cell differentiation by utilizing a combination of cellular, molecular genetics, Biochemical and computational tools in combination with next generation sequencing based chromatin structure analysing methods. Successful candidates shall pursue project related to either experimental or computational analysis of genome and Epigenomics data derived from human and mouse cells. Experience in Computational biology, bioinformatics, statistics, machine learning and algorithmic development is required. Knowledge of programming languages (e.g. C, C++, Perl, Python, Ruby etc.) and statistical framework (e.g. R, matlab, etc.) is preferable. Basic understanding of molecular biology will be an added advantage.

Interested candidates with the above mentioned qualification can send their curriculum vitae to Dr. K. Sreenivasulu, Department of Animal Biology, School of Life Sciences, South campus, University of Hyderabad or via email at positionssklab@gmail.com or svksl@uohyd.ernet.in.

Candidates with CSIR/UGC/ICMR/DBT/BINC qualifications if interested in above mentioned area of research are welcomed to approch principal investigator for a position leading to PhD. Last date for submission of applications is 17/06/2016. Eligible candidates will be called for an interview and they should carry all original certificates of the qualifying exam. No TA/ DA will be paid for attending the interview or at the time of joining the post.

Advertisement: http://www.uohyd.ac.in/images/recruitment/jrf_260516.pdf

HistoneDB 2.0 – with variants

Anjana — Fri, 03 Jun 2016 05:06:20 -0500

This histone database can be used to explore the diversity of histone proteins and their sequence variants in many organisms. The resource was established to better understand how sequence variation may affect functional and structural features of nucleosomes. To get started, select a histone type to explore its variants.

More at http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/projects/HistoneDB2.0/index.fcgi/browse/

MutaBind

Jit — Mon, 06 Jun 2016 13:34:09 -0500

MutaBind is a new computational method and server created through NCBI research efforts that maps mutations on a protein structural complex, calculates changes in binding affinity, identifies deleterious mutations and produces a downloadable mutant structural model. http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/

MutaBind guides you through this process, step by step, starting with selecting a protein complex and inputting PDB code or uploading PDB files. You can also retrieve results with a job ID number, view help documents, and review the MutaBind method and references.

More at http://www.ncbi.nlm.nih.gov/projects/mutabind/index.fcgi/

Guest Faculty Centre for Bioinformatics at Pondicherry University

Wed, 15 Jun 2016 03:44:31 -0500

Guest Faculty Centre For Bioinformatics Jobs opportunity in Pondicherry University
Qualification : M.Phil. (with NET/SLET)/ M.Tech. / M.E. in Computer Science with a minimum of 55% of marks as per UGC norms.
Desirable : Ph.D and Teaching experience in Perl and Java programming.
Honorarium : Rs. 1,000/- per lecture (subject to a maximum of Rs. 25,000/- per month)
How to apply
Walk-in-Interview will be held on 29.06.2016 (Wednesday) at 2:30 P.M at the office of Centre for Bioinformatics, Pondicherry University, Puducherry — 605 014. Interested eligible candidates may attend the Walk-in-Interview along with all original certificates, self attested photocopies and testimonials with a copy of their bio-data. Candidates reporting after 2:30 P.M will not be entertained.

More at http://www.pondiuni.edu.in/news?quicktabs_2=5#quicktabs-2

DarkHorse

Jit — Wed, 22 Jun 2016 05:37:38 -0500

DarkHorse is a bioinformatic method for rapid, automated identification and ranking of phylogenetically atypical proteins on a genome-wide basis. It works by selecting potential ortholog matches from a reference database of amino acid sequences, then using these matches to calculate a lineage probability index (LPI) score for each genome protein.

LPI scores are inversely proportional to the phylogenetic distance between database match sequences and the query genome. These scores are useful not only for large-scalede novo predictions of horizontally transferred proteins, but can also serve as an independent quality control test for potential horizontal transfer candidates identified by alternative methods, especially those based on nucleic acid signatures. Candidates having high LPI scores are unlikely to have been horizontally transferred, since they are highly conserved among closely related organisms.

One unique and powerful feature of the DarkHorse HGT Candidate database is the opportunity to explore the phylogenetic background of potential HGT donors as well as recipients. The breadth of the database allows not only query sequences, but also their database match partners to be evaluated for sequence similarity or novelty compared to taxonomically related organisms.

DarkHorse is configurable for varying degrees of phylogenetic granularity and protein sequence conservation. Users should consult the references cited below for a complete explanation of parameter selection and result interpretation. A brief tutorial page is also available on-line.

Address of the bookmark: http://darkhorse.ucsd.edu/download.html

Cheatsheet for Linux !!

Jit — Wed, 22 Jun 2016 07:55:06 -0500

Linux Commands Cheat Sheet

    File System

    ls — list items in current directory

    ls -l — list items in current directory and show in long format to see perimissions, size, an modification date

    ls -a — list all items in current directory, including hidden files

    ls -F — list all items in current directory and show directories with a slash and executables with a star

    ls dir — list all items in directory dir

    cd dir — change directory to dir

    cd .. — go up one directory

    cd / — go to the root directory

    cd ~ — go to to your home directory

    cd - — go to the last directory you were just in

    pwd — show present working directory

    mkdir dir — make directory dir

    rm file — remove file

    rm -r dir — remove directory dir recursively

    cp file1 file2 — copy file1 to file2

    cp -r dir1 dir2 — copy directory dir1 to dir2 recursively

    mv file1 file2 — move (rename) file1 to file2

    ln -s file link — create symbolic link to file

    touch file — create or update file

    cat file — output the contents of file

    less file — view file with page navigation

    head file — output the first 10 lines of file

    tail file — output the last 10 lines of file

    tail -f file — output the contents of file as it grows, starting with the last 10 lines

    vim file — edit file

    alias name 'command' — create an alias for a command
    System

    shutdown — shut down machine

    reboot — restart machine

    date — show the current date and time

    whoami — who you are logged in as

    finger user — display information about user

    man command — show the manual for command

    df — show disk usage

    du — show directory space usage

    free — show memory and swap usage

    whereis app — show possible locations of app

    which app — show which app will be run by default
    Process Management

    ps — display your currently active processes

    top — display all running processes

    kill pid — kill process id pid

    kill -9 pid — force kill process id pid
    Permissions

    ls -l — list items in current directory and show permissions

    chmod ugo file — change permissions of file to ugo - u is the user's permissions, g is the group's permissions, and o is everyone else's permissions. The values of u, g, and o can be any number between 0 and 7.

    7 — full permissions

    6 — read and write only

    5 — read and execute only

    4 — read only

    3 — write and execute only

    2 — write only

    1 — execute only

    0 — no permissions

    chmod 600 file — you can read and write - good for files

    chmod 700 file — you can read, write, and execute - good for scripts

    chmod 644 file — you can read and write, and everyone else can only read - good for web pages

    chmod 755 file — you can read, write, and execute, and everyone else can read and execute - good for programs that you want to share
    Networking

    wget file — download a file

    curl file — download a file

    scp user@host:file dir — secure copy a file from remote server to the dir directory on your machine

    scp file user@host:dir — secure copy a file from your machine to the dir directory on a remote server

    scp -r user@host:dir dir — secure copy the directory dir from remote server to the directory dir on your machine

    ssh user@host — connect to host as user

    ssh -p port user@host — connect to host on port as user

    ssh-copy-id user@host — add your key to host for user to enable a keyed or passwordless login

    ping host — ping host and output results

    whois domain — get information for domain

    dig domain — get DNS information for domain

    dig -x host — reverse lookup host

    lsof -i tcp:1337 — list all processes running on port 1337
    Searching

    grep pattern files — search for pattern in files

    grep -r pattern dir — search recursively for pattern in dir

    grep -rn pattern dir — search recursively for pattern in dir and show the line number found

    grep -r pattern dir --include='*.ext — search recursively for pattern in dir and only search in files with .ext extension

    command | grep pattern — search for pattern in the output of command

    find file — find all instances of file in real system

    locate file — find all instances of file using indexed database built from the updatedb command. Much faster than find

    sed -i 's/day/night/g' file — find all occurrences of day in a file and replace them with night - s means substitude and g means global - sed also supports regular expressions
    Compression

    tar cf file.tar files — create a tar named file.tar containing files

    tar xf file.tar — extract the files from file.tar

    tar czf file.tar.gz files — create a tar with Gzip compression

    tar xzf file.tar.gz — extract a tar using Gzip

    gzip file — compresses file and renames it to file.gz

    gzip -d file.gz — decompresses file.gz back to file
    Shortcuts

    ctrl+a — move cursor to beginning of line

    ctrl+f — move cursor to end of line

    alt+f — move cursor forward 1 word

    alt+b — move cursor backward 1 word

Machine Learning !!!

Gudiya Pal — Fri, 01 Jul 2016 12:57:12 -0500

In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.

Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.

Address of the bookmark: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/