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BioMiner & Personalized Medicine: A new perspective

Dr. Muniba Faiza

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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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[Tutorial] How to install 3Dmapper on Ubuntu (Linux)?

Dr. Muniba Faiza

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Installing 3Dmapper on Ubuntu (Linux).

Understanding the relationship between genes and proteins is crucial for elucidating biological processes, and disease mechanisms, and developing targeted therapies. A new tool developed by Yang et. al., [1], provides a better solution to map annotated positions and variants to protein structures automatically. 3Dmapper is a stand-alone tool based on R and Python programming languages that map annotated genomic variants or positions to protein structures [1]. In this article, we will install 3Dmapper on Ubuntu (Linux).

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CMake installation and upgrade: What worked & what didn’t?!

Dr. Muniba Faiza

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CMake installation and upgrade: What worked & what didn’t?!

CMake is a widely used cross-platform build system that automates the process of compiling and linking software projects. In bioinformatics, CMake can be utilized to manage the build process of software tools and pipelines used for data analysis, algorithm implementation, and other computational tasks. However, managing the versions of CMake or upgrading it on Ubuntu (Linux) can be a trivial task for beginners. In this article, we provide methods for installing and upgrading CMake on Ubuntu.

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Bioinformatics Programming

Free_Energy_Landscape-MD: Python package to create Free Energy Landscape using PCA from GROMACS.

Dr. Muniba Faiza

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In molecular dynamics (MD) simulations, a free energy landscape (FEL) serves as a crucial tool for understanding the behavior of molecules and biomolecules over time. It is difficult to understand and plot a meaningful FEL and then extract the time frames at which the plot shows minima. In this article, we introduce a new Python package (Free_Energy_Landscape-MD) to generate an FEL based on principal component analysis (PCA) from MD simulation done by GROMACS [1].

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Bioinformatics News

VS_Analysis: A Python package to perform post-virtual screening analysis

Dr. Muniba Faiza

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VS_Analysis: A Python package to perform post-virtual screening analysis

Virtual screening (VS) is a crucial aspect of bioinformatics. As you may already know, there are various tools available for this purpose, including both paid and freely accessible options such as Autodock Vina. Conducting virtual screening with Autodock Vina requires less effort than analyzing its results. However, the analysis process can be challenging due to the large number of output files generated. To address this, we offer a comprehensive Python package designed to automate the analysis of virtual screening results.

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Bioinformatics Programming

vs_interaction_analysis.py: Python script to perform post-virtual screening analysis

Dr. Muniba Faiza

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vs_interaction_analysis.py: Python script to perform post-virtual screening analysis

Analyzing the results of virtual screening (VS) performed with Autodock Vina [1] can be challenging when done manually. In earlier instances, we supplied two scripts, namely vs_analysis.py [2,3] and vs_analysis_compounds.py [4]. This time, we have developed a new Python script to simplify the analysis of VS results.

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Software

How to install Interactive Genome Viewer (IGV) & tools on Ubuntu?

Dr. Muniba Faiza

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How to install Interactive Genome Viewer (IGV) & tools on Ubuntu?

Interactive Genome Viewer (IGV) is an interactive tool to visualize genomic data [1]. In this article, we are installing IGV and tools on Ubuntu desktop.

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MD Simulation

[Tutorial] Installing VIAMD on Ubuntu (Linux).

Dr. Muniba Faiza

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[Tutorial] Installing VIAMD on Ubuntu (Linux).

Visual Interactive Analysis of Molecular Dynamics (VIAMD) is a tool that allows the interactive analysis of molecular dynamics simulations [1]. In this article, we are installing it on Ubuntu (Linux).

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Docking

[Tutorial] Performing docking using DockingPie plugin in PyMOL.

Dr. Muniba Faiza

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[Tutorial] Performing docking using DockingPie plugin in PyMOL.

DockingPie [1] is a PyMOL plugin to perform computational docking within PyMOL [2]. In this article, we will perform simple docking using DockingPie1.2.

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Docking

How to install the DockingPie plugin on PyMOL?

Dr. Muniba Faiza

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How to install DockingPie plugin on PyMOL?

DockingPie [1] is a plugin of PyMOL [2] made to fulfill the purpose of docking within the PyMOL interface. This plugin will allow you to dock using four different algorithms, namely, Vina, RxDock, SMINA, and ADFR. It will also allow you to perform flexible docking. Though the installation procedure is the same for all OSs, in this article, we are installing this plugin on Ubuntu (Linux).

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Video Tutorial: Calculating binding pocket volume using PyVol plugin.

Dr. Muniba Faiza

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Calculate Binding Pocket Volume in Pymol (using PyVol plugin).

This is a video tutorial for calculating binding pocket volume using the PyVol plugin [1] in Pymol [2].

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Software

How to generate topology from SMILES for MD Simulation?

Dr. Muniba Faiza

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How to generate topology from SMILES for MD Simulation?

If you need to generate the topology of molecules using their SMILES, a simple Python script is available.

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Software

[Tutorial] Installing jdock on Ubuntu (Linux).

Dr. Muniba Faiza

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[Tutorial] Installing jdock on Ubuntu (Linux).

jdock is an extended version of idock [1]. It has the same features as the idock along with some bug fixes. However, the binary name and the GitHub repository names are changed. We are installing jdock on Ubuntu (Linux).

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Software

How to upgrade cmake on Ubuntu (Linux)?

Dr. Muniba Faiza

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How to upgrade cmake on Ubuntu/Linux?

In bioinformatics, cmake is used to install multiple software including GROMACS, jdock, and so on. Here is a short tutorial on how to upgrade cmake on Ubuntu and get rid of the previous version. (more…)

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Software

How to install GMXPBSA on Ubuntu (Linux)?

Dr. Muniba Faiza

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How to install GMXPBSA on Ubuntu (Linux)?

GMXPBSA is a tool to calculate binding free energy [1]. It is compatible with Gromacs version 4.5 and later. In this article, we will install GMXPBSA version 2.1.2 on Ubuntu (Linux).

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Docking

[Tutorial] Installing Pyrx on Windows.

Dr. Muniba Faiza

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[Tutorial] Installing Pyrx on Windows.

Pyrx [1] is another virtual screening software that also offers to perform docking using Autodock Vina. In this article, we will install Pyrx on Windows. (more…)

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MD Simulation

How to solve ‘Could NOT find CUDA: Found unsuitable version “10.1”‘ error during GROMACS installation?

Dr. Muniba Faiza

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How to solve ‘Could NOT find CUDA: Found unsuitable version “10.1”‘ error during GROMACS installation?

Compiling GROMACS [1] with GPU can be trivial. Previously, we have provided a few articles on the same. In this article, we will solve an error frequently occurring during GROMACS installation.

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Software

Installing Autodock4 on MacOS.

Dr. Muniba Faiza

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Installing Autodock4 on MacOS

Previously, we installed the Autodock suite [1] on Ubuntu. Visit this article for details. Now, let’s install it on MacOS.

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Docking

How to install Autodock4 on Ubuntu?

Dr. Muniba Faiza

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How to install Autodock4 on Ubuntu?

Autodock suite is used for docking small molecules [1]. Recently, Autodock-GPU [2] is developed to accelerate the docking process. Its installation is described in this article. In this tutorial, we will install Autodock 4.2.6 on Ubuntu.

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Software

DS Visualizer: Uses & Applications

Dr. Muniba Faiza

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DS Visualizer: Uses & Applications

Discovery Studio (DS) Visualizer (from BIOVIA) is a visualization tool for viewing, sharing, and analyzing proteins [1]. Here are some uses and applications of DS Visualizer.

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Software

Protein structure & folding information exploited from remote homologs.

Dr. Muniba Faiza

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protein structure & folding prediction using remote homologs

Remote homologs are similar protein structures that share similar functions, but there is no easily detectable sequence similarity in them. A new study has revealed that the protein folding information can be exploited from remote homologous structures. A new tool is developed to recognize such proteins and predict their structure and folding pathway. (more…)

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