Biology subjects

Rafsanjani, M. R.

Publications and source records attributed to Rafsanjani, M. R..

3 recordsLinked to original sources

bioRxiv2022

Discovering triple negative breast cancers (TNBC) transcriptomic profiles via massive screening of single cell RNA-sequencing (scRNA-seq) datasets.

Triple negative breast cancers (TNBC) account for 18% of the breast cancer patients in Malaysia and also account for one of the worst prognoses albeit it is the rare cancer types. TNBC is defined as breast cancers that tested negative on all 3 tests of oestrogen/progesterone (ER/PR) receptor and human epidermal growth receptor 2 (HER2). Understanding the TNBC biology is challenging due to the fact of multiple subtypes and its heterogeneity in patient samples. Here we attempt to examine the transcriptional profiling of TNBC using the single cell RNA-sequencing (scRNA-seq) analysis of different publicly available TNBC datasets. In comparison to bulk-RNA, scRNA-seq allowed the mapping of transcriptional profiling of TNBC at the single cell resolution and able to accurately pinpoint pan-transcriptional markers of TNBC.

cancer biology↗

bioRxiv2022

ScrapPaper: A web scrapping method to extract journal information from PubMed and Google Scholar search result using Python.

This paper introduces a program called ScrapPaper, a simple Python script that use web-scraping method to extract journal information from PubMed and Google Scholar search results page. Currently the motivation behind the program development is trying to solve a problem to obtain scientific literatures information especially the title and link and save as a list for further use such as in meta-analysis and comparative study of literatures. ScrapPaper advantage that it is simple to use with no prior programming experience and get the results ready within minutes (depending on the total search result). Web-scrapping is a very powerful method to extract information from the web and ScrapPaper employ several server friendly approaches accessing both PubMed and Google Scholar site. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

bioinformatics↗

bioRxiv2021

Analysing and identifying miRNAs from RNA-seq data using miRDeep2 tool in Galaxy, a practical guide.

Micro-RNAs (miRNAs) analysis from RNA-seq experiment data provides additional depth into the cellular gene regulation. Such analysis has been simplified using miRDeep2 tool available in freely accessible Galaxy Europe server and miRBase database that compiled the miRNAs in many organisms. Here, we are describing a step by step protocol on how to ultilised the tool and most importantly on how to prepared and compiled miRDeep2 results to be used for downstream analysis such as investigating the differential expression of the detected miRNAs. Currently miRDeep2 miRNAs count result output in the Galaxy are in the broken HTML page and processing such data are troublesome for further analysis unless the user setting up their software dependencies for the tool to run. Hence, we proposed a method to process this output so that it is usable for downstream processing without a single coding required.

bioinformatics↗