Bio Saga Blog - A Chronicle of Life Sciences & Informatics

              Know About Our Workshop On Bioinformatics and Protein Structure Prediction 10th to 12th May 2019 | Pune, India | 09:30 AM - 05:00 PM Our 3 day comprehensive workshop on Bioinformatics and Protein Structure Prediction aims at providing systematic Hands-on-Training on Protein visualization, mutation & other manipulations.Understand concept of in-silico protein modelling using servers & software’s.Understanding concept of protein motif and domains.Understanding concept of protein structure prediction by Modeller COMPREHENSIVE & SEQUENTIAL SESSIONS ON: ▪ Introduction to Biological databases ▪ Multiple Sequence Alignment – CLUSTALW ▪ Introduction to Proteins & Protein Databases-UNIPROT ▪ Study of proteins and their structures ▪ Protein Secondary Structure Prediction tools ▪ Protein Tertiary Structure Prediction using Servers & Modeller ▪ Protein Structure Validation ...

Pred_PPI is a web-based system that serves for predicting PPIs from different organisms. This server is freely available to any researcher wishing to use it for non-commercial purposes. Based on auto covariance (AC) and support vector machine (SVM), this tool is capable of predicting PPIs for any target protein pair only using their primary sequences, and assigning an interaction probability to each SVM prediction as well. So the user can use this tool to predict novel PPIs with high confidence. Protein-protein interactions (PPIs) are essential for almost all cellular processes, such as metabolic cycles, DNA transcription and replication, different signaling cascades and so on. However the biochemical methods are all time-consuming and expensive, so current PPI pairs elucidated by experiments are absolutely insufficient compared to the complete PPI networks . Consequently it is increasing important to develop computational tools for effectively identifying PPIs. Check out this one t...

The emergence of “Systems Biology” in recent years highlights the systematic viewpoint of bio-system modeling. Building on such a background, Dual Descriptor Method, a generic methodology for biological sequence analysis is proposed. From a systematic perspective, Dual Descriptor is defined as a two element set of Composition Weight Map and Position Weight Function which aim at reflecting the composition and permutation information of a sequence. An alternate training algorithm is provided to get an optimum description of the building patterns of the sequences. In this paper , dual descriptor method has been applied to the analysis of two typical problems of molecular biology: gene identification and the prediction of protein function. Satisfactory and insightful results are achieved. Owing to the generality of this methodology, dual descriptor method has wide application perspective for many problems of pattern recognition, especially those involved in “Systems Biology”. Be a part of ...