Proteomics journals 2018

We are back with the updated list of journals in the field of proteomics for 2018. Please use the comment section to suggest journals that are missing from the list.

Journal name	Website link	Impact factor	Publisher	Author Guidelines link
Genomics, Proteomics & Bioinformatics	Link	6.615	Elsevier	Link
Molecular and Cellular Proteomics	Link	5.232	American Society for Biochemistry and Molecular Biology	Link
Journal of Proteome Research	Link	3.95	ACS Publications	Link
Journal of Proteomics	Link	3.722	Elsevier	Link
Proteomics - Clinical Applications	Link	3.567	Wiley	Link
Proteomics	Link	3.532	Wiley	Link
Clinical Proteomics	Link	3.516	Springer Nature	Link
Expert Review of Proteomics	Link	3.489	Taylor & Francis Online	Link
Comparative Biochemistry and Physiology D-Genomics & Proteomics	Link	2.913	Elsevier	Link
Biochimica Et Biophysica Acta-Proteins and Proteomics	Link	2.609	Elsevier	Link
Cancer Genomics & Proteomics	Link	2.432	International Institute of Anticancer Research (IIAR)	Link
Proteome Science	Link	1.769	Springer Nature	Link
Current Proteomics	Link	0.606	Bentham Science	Link
EuPA Open Proteomics	Link	-NA-	Elsevier	Link
Journal of Proteins and Proteomics	Link	-NA-	Serials Publications (Proteomics Society, India)	Link

Workshop on mass spectrometry-based proteomics at Center for Systems Biology and Molecular Medicine, Mangalore, India

Center for Systems Biology and Molecular Medicine (CSBMM) at Yenepoya Research Centre is an advanced multidisciplinary research center with state-of-the-art infrastructure to carry out genomics, proteomics and metabolomics investigations. As a part of the academic program of Yenepoya (Deemed to be University), scientists at CSBMM will share their expertise in high- resolution mass spectrometry-based proteomic technologies with young researchers of India through this workshop. 

The organizers are part of the consortium that previously published the draft map of the human proteome in Nature (https://www.nature.com/articles/nature13302).

Workshop on Fundamentals of Mass Spectrometry-based Proteomics for Beginners

Date: August 23-25, 2018, 

Venue: Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore, India

Link: https://proteomicsworld.blogspot.com/

Targeted Proteomics Course at ETH, Zurich

Institute of Molecular Systems Biology is organizing a targeted proteomics course at ETH, Zurich between 8-12 February, 2016.

The deadline for application is on 15 November, 2015.

For more details, visit this link

How to stop Excel converting your SEPT1 gene to September1

Several scientists around the world use Microsoft Excel to visualize or process their data. Excel can be fun to use when you know the commands well. However, when it comes to sorting gene symbols or creating protein databases using Excel, it may cause several problems. Some of the gene symbols are always converted into dates. 

For example:

SEPT1 becomes Sep-01

MARC1 becomes Mar-01

MARCH1 becomes Mar-01

This is true for the SEPT, MARC1 and MARCH1 gene families. 

Most often, you don't know that this has happened and you are forced to erroneously conclude that you haven't identified these genes in your data.

You can manually correct these by adding a single quote (') symbol before the gene name. This is very tedious and troublesome for downstream data processing. To make it worse, I found out that Excel does not have an option to turn off this annoying transmogrification.

By trial and error, I found out  a perfect way to overcome this problem in Excel.

STEP1: Save your database file in CSV (Comma separated) or TSV (Tab separated) formats

STEP 2: Start the "Import Text File" wizard by going to the "Data" Tab and clicking "From Text"

STEP 3: Select your CSV or TSV file and click "Import".

STEP 4: Choose the "delimited" option and click "Next"

STEP 5: Select "Comma" (if you used CSV file) or "Tab" (if you used TSV file) and click "Next"

STEP 6: Select the "Gene Symbol" column in the "Data Preview" and select the option "Text" in the "Column data format"

STEP 7: Click "Finish" and then click "OK".

Now scroll back and check that SEPT1 has not been touched by Excel.

If you want a video on it, use this link

RefSeq72 is out. Time to update your databases

RefSeq72 has been now released. Follow this link for more information.

Phosphoproteomic analysis of breast cancer cells to identify targets for tamoxifen resistance

A new study on the phosphoproteomics analysis of tamoxifen-resistant breast cancer cells has been published from Dr. Akhilesh Pandey's lab in the recent issue of Molecular and Cellular Proteomics. 

In this study, MCF7 breast cancer cell lines were chronically treated with tamoxifen for 6 months to acquire resistance. SILAC-based quantitative phosphoproteomic profiling  of treated and untreated cells with a Orbitrap Velos mass spectrometer identified over 5,000 unique phosphopeptides, with over 2,000 peptides differentially phosphorylated between the two conditions. 

Focal adhesion pathway was found to be enriched by pathway analysis. Silencing FAK2 suppressed cell proliferation and tumor formation. Further, high FAK2 expression was found to correlate with shorter metastasis-free survival in tamoxifen-treated breast cancer patients. 

The authors suggest that FAK2 could serve as a potential therapeutic target for management of hormone refractory breast cancers.