For updates or inquiries:
For software source code or troubleshooting, please do not hesitate to contact me, e-mail haithamsobhy at gmail dot com, and twitter: @hsob23.
SourceForge page: https://sourceforge.net/u/hsobhy/profile/
For more details, please see the publications in "Articles" page.
Gemi
Gemi is an automated, fast, and easy-to-use bioinformatics tool with a user-friendly interface to design primers and probes for polymerase chain reaction (PCR). Gemi accepts multiple aligned and long DNA and RNA sequences with degenerate nucleotide (non-A/C/G/T bases). Gemi can be used for quantitative, real-time and conventional PCR (qPCR, rt-PCR, etc.), and Sanger sequencing. Gemi can parse large dataset of sequences efficiently.
Article: Gemi: PCR primers prediction from multiple alignments; Comparative and Functional Genomics; vol. 2012, Article ID 783138, 2012. doi: 10.1155/2012/783138; PMID: 23316117, PMCID: PMC3535827
Please, click HERE to download
For Python code, click HERE to download
Shetti
Shetti is an easy and simple tool created for experimental biologists to analyze, search or manipulate large datasets of sequences efficiently, without the need to write additional scripts or codes. Shetti parses UniProt Knowledgebase and NCBI GenBank flat files and visualizes them as a table. Shetti can be used to construct a universal consensus for genes and molecular signatures for proteins based on their physical characteristics.
Article: Shetti, a simple tool to parse, manipulate and search large datasets of sequences; Microbial Genomics Journal; 2015. doi: 10.1099/mgen.0.000035; PMID: 28348820, PMCID: PMC5320677
Please, click HERE to download
Shetti-Motif
Short linear motifs / domains (SLiM) facilitate the functions and interactions of the proteins. Finding functional motifs in protein sequences could predict the putative cellular roles or characteristics of hypothetical proteins. ShettiMotif, which is an interactive tool to (i) searches for motifs containing repeated residues (e.g. Leu-, SR-, PEST-rich motifs, etc.), (ii) searches for multiple pre-defined consensus patterns or experimentally validated functional motifs in large datasets protein sequences (proteome-wide), (iii) map UniProt and PROSITE flat files. ShettiMotif can parse large dataset of sequences efficiently.
Article: H Sobhy; A bioinformatics pipeline to search functional motifs within whole proteome data; poxviruses a case study; Virus Genes, 2016; doi: 10.1007/s11262-016-1416-9; PMID: 28000080, PMCID: PMC5357487
Please, click HERE to download