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BioMiner & Personalized Medicine: A new perspective

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Personalized medicines have become a very important part of the medicine world now a days. They are also known as ‘Individualized Medicines’. Personalized medicines allow a doctor to prescribe more specific and efficient medicines to a particular patient. This concept has created many more opportunities and aspects in the medicine world.

Personalized medicine concept is accomplished by obtaining high-throughput data sets from genomics, transcriptomics, proteomics and metabolomics, but more specifically it requires the ‘cross-omics’, i.e., linkage between transcriptomics, proteomics and metabolomics. Currently, there are simple web-based tools which do not allow much access to the high throughput datasets from the omics. But a new novel web based tool “Biominer” has been launched recently which provides access to a wide variety of high-throughput datasets. This tool was developed within the scope of an international and interdisciplinary project (SYSTHER).

Biominer provides the user various facilities with convenient tools which help them to analyze the high-throughput datasets and provides a deep insight for complex cross-omics datasets with enhanced visualization abilities.

Since Biominer was developed under Systher (System Biology  Tools Development for Cell Therapy and Drug Development – www.systher.eu) project so its main focus is on cancer.

Public data repositories such as Gene Expression Omnibus (GEO) and ArrayExpress for microarray data, PRoteomics IDEntifications (PRIDE) for proteomics data, or Sequence Read Archive (SRA) of NCBI are used to store the biological high-throughput datasets for next- generation sequencing. The only limitation with these repositories is that they store biological data of a dedicated set of single omic type and do not support the cross-omics.

A database namely, SystherDB has been developed in which the stored data is well presented and easily accessible, and whose data is mined and analyzed by the BioMiner tools. A public instance of BioMiner is freely available online. It currently contains 18 different studies, with almost 4,000 microarrays and more than 187 Mio measured values of genes, proteins, or metabolites. Since BioMiner was developed in the SYSTHER project, most of the studies are focused on the glioblastoma multiforme (GBM).

Fig.1

Fig.1 Workflow of BioMiner

FEATURES:

  1. BioMiner uses Google Web Toolkit (GWT) for the graphical user interface (GUI).
  2. A separate MySQL database is created which is manually curated and used to store the Experimental data from genomics, proteomics and metabolomics.
  3. Data import has to be performed by a dedicated specialist to ensure the data consistency.
  4. Response time is with in just a few seconds, for this purpose special indexing methods are implemented.
  5. Metabolite data are annotated using three different identifier systems: Golm Metabolome Database, Human Metabolome Database (HMDB), and Kyoto Encyclopedia of Genes and Genomes (KEGG).
  6. Predefined cross-omics relationship (e.g., a mapping of metabolites onto genes or vice versa) among the biological datasets.
  7. Pathway and functional information from Reactome, KEGG, and Wiki- Pathways.
  8. Gene Ontology is also supported.
  9. Correlation analyses (statistical analysis of any two variables) are based on Pearson correlation coefficients.
  10. Correlations are calculated for high-variance genes (by default top 500 genes).
  11. BioMiner complies with public data management standards such as Minimum Information About a Microarray Experiment (MIAME), Minimum Information About a Proteomics Experiment (MIAPE), and Minimum Information About a Metabolomics Experiment (MIAMET).
  12. ENSEMBL database is used for cross-mapping between the genes and proteins.
  13. Cross-mapping between the genes and metabolites the combined information of ConsensusPathDB and HMDB is used.

                                              A

Fig.2

Fig2 . Data mining with Biominer. screenshots of different results from data mining with Biominer including the following: (a) study overview,  (B) detection of differentially expressed genes, (C) correlation of gene expression and survival time, (d) identification of significantly enriched pathways, (e) visual pathway inspection based on predefined layouts, and (f) biomolecule comparison of gene and protein expression. results are typically presented in synchronized, parallel views composed of a table and a plot.

Fig.3

Fig3. Pathway visualization. Interactive pathway visualization of the cell cycle pathway from WikiPathways repository.

BioMiner is a web-based tool which provides various tools for studying the statistical analysis and a deep insight of transcriptomics, proteomics and metabolomics with cross-omics concept. Results are presented in two parallel views composed of a table and a plot. Both views are interactive and user-defined selections can be synchronized. Pathway visualization is achieved by extending the PathVisio library. It also provides clinicians and physicians a platform integrating high-throughput data together with clinical parameters, thereby leading to better personalized medicines.

References:

Chris Bauer1, Karol stec1, alexander Glintschert1, Kristina Gruden2, Christian schichor3, michal or-Guil4,5, Joachim selbig6 and Johannes schuchhardt1

Dr. Muniba is a Bioinformatician based in New Delhi, India. She has completed her PhD in Bioinformatics from South China University of Technology, Guangzhou, China. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba

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DS Visualizer: Uses & Applications

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DS Visualizer: Uses & Applications

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Protein structure & folding information exploited from remote homologs.

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protein structure & folding prediction using remote homologs

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RNA-seq analysis

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Pathonoia- A new tool to detect pathogens in RNA-seq data.

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AlphaFill- New algorithm to fill ligands in AlphaFold models.

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AlphaFill- New algorithm to fill ligands in AlphaFold models.

AlphaFold is a popular artificial intelligence based protein prediction tool [1]. Though it predicts good protein structures, it lacks the capability to predict the small molecules present in the structure such as ligands. For this purpose, AlphaFill is introduced by Hekkelman et al.,[2]. (more…)

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How to calculate binding pocket volume using PyVol plugin in PyMol?

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How to calculate binding pocket volume using PyVol plugin in PyMol?

Previously, we provided a tutorial for PyVol plugin [1] installation. In this article, we will calculate the binding pocket volume of protein using the same plugin in PyMol [2]. (more…)

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How to generate electron density map using Pymol?

Electron density maps are available for most of the protein structures in PDB. Therefore, in this article, we are using PDB to generate electron density maps in Pymol.

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Software

Installing PyVOL plugin in Pymol on Ubuntu (Linux).

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Installing PyVOL plugin in Pymol on Ubuntu (Linux).

PyVOL [1] is an excellent plugin of Pymol [2] for pocket visualization of proteins. In this article, we will install the PyVOL plugin in Pymol on Ubuntu. (more…)

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How to install Kpax on Ubuntu (Linux)?

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Kpax is a bioinformatics program to search and align protein structures [1]. It is currently available for Linux platforms only. In this article, we are going to install the latest version of Kpax (5.1.3) on Ubuntu (Linux). (more…)

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Secondary structure

How to run do_dssp command (mkdssp) in Gromacs 2022?

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How to run do_dssp command in Gromacs 2022?

In the latest version of GROMACS (2022) [1], there are some issues regarding the gmx do_dssp command. Apparently, this command either does not run displaying a fatal error, or if it runs then it does not read any frame from MD simulation files. In this article, we are going to run the same command for GROMACS 2022. (more…)

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Installing SMINA on Ubuntu (Linux).

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SMINA is a fork of AutoDock Vina supporting better scoring function and high-performance energy minimization [1]. In this article, we are going to install SMINA on Ubuntu (Linux). (more…)

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How to install ClusCo on Ubuntu (Linux)?

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ClusCo is a bioinformatics software to perform clustering and comparison of protein models [1]. In this article, we are going to install ClusCo on Ubuntu (Linux). (more…)

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Software

How to run LigAlign plugin on Pymol?

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How to run LigAlign plugin on Pymol?

Running a plugin on an old version of Pymol [1] can give you multiple errors that are not easy to troubleshoot. For example, LigAlign plugin [2] runs on an old version of Pymol. Previously, we explained how to install LigAlign on Pymol. In this article, we will run the LigAlign command on Pymol. (more…)

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How to install the LigAlign plugin on Pymol on Ubuntu (Linux)?

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How to install the LigAlign plugin on Pymol on Ubuntu (Linux)?

Few errors appear when we try to run the LigAlign plugin [1] in Pymol [2]. For example, if you try to run the ligand_alignment plugin, it will give you multiple errors including “Unable to initialize LigAlign v1.00“, or “can’t run LigAlign v1.00” or “incorrect Python syntax” or “Plugin has been installed but initialization failed“. In this article, we explain the reason for this issue and how you can rectify these errors. (more…)

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Software

How to install multiple Pymol versions on Ubuntu (Linux)?

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Installing multiple versions of Pymol on Ubuntu

Sometimes we need to access old versions of Pymol [1]. Running some plugins on Pymol is difficult due to Python incompatibility. New Pymol versions require Python 3.x whereas older versions run on Python 2.x. Therefore, we need to maintain multiple versions of Pymol on a single system. In this article, we will install Pymol 1.7.x along with the latest version (Pymol 2.5.2) on Ubuntu. Later, we will create shortcuts for them.

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Software

[Tutorial] Installing Pymol on Mac OS.

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Previously, we provided a tutorial for Pymol installation on Ubuntu. In this article, we are going to install Pymol on Mac OS. (more…)

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How to install VMD on Ubuntu?

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How to install VMD on Ubuntu?

In this article, we are going to install VMD [1] on Ubuntu. (more…)

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MD Simulation

How to install GROMACS on Apple M1 (MacOS)?

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Installing GROMACS on Apple M1 (MacOS)

We have provided a few articles on GROMACS installation on Ubuntu. In this article, we are going to install GROMACS [1] on Mac OS. (more…)

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Software

PyMol: Uses & Applications

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PyMol: Uses & Applications

PyMol is one of the most widely used bioinformatics software. Generally, it is used as a molecular viewer to visualize macromolecules and small molecules. In this article, we are discussing several uses and applications of PyMol. (more…)

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MD Simulation

How to take snapshots of structure at specific times in GROMACS?

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How to take snapshots of structure at specific times in GROMACS?

It is important to see the behavior of protein during an MD simulation. This can be achieved by taking snapshots in the form of PDB format. In this article, we have provided a few commands that you can use to take snapshots of a complete system or protein during MD simulation. (more…)

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