CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity

Drug therapy is vital in cancer treatment. Accurate analysis of drug sensitivity for specific cancers can guide healthcare professionals in prescribing drugs, leading to improved patient survival and quality of life. However, there is a lack of web-based tools that offer comprehensive visualization and analysis of pancancer drug sensitivity. We gathered cancer drug sensitivity data from publicly available databases (GEO, TCGA and GDSC) and developed a web tool called Comprehensive Pancancer Analysis of Drug Sensitivity (CPADS) using Shiny. CPADS currently includes transcriptomic data from over 29 000 samples, encompassing 44 types of cancer, 288 drugs and more than 9000 gene perturbations. It allows easy execution of various analyses related to cancer drug sensitivity. With its large sample size and diverse drug range, CPADS offers a range of analysis methods, such as differential gene expression, gene correlation, pathway analysis, drug analysis and gene perturbation analysis. Additionally, it provides several visualization approaches. CPADS significantly aids physicians and researchers in exploring primary and secondary drug resistance at both gene and pathway levels. The integration of drug resistance and gene perturbation data also presents novel perspectives for identifying pivotal genes influencing drug resistance. Access CPADS at https://smuonco.shinyapps.io/CPADS/ or https://robinl-lab.com/CPADS.

Computational Approaches Drive Developments in Immune-Oncology Therapies for PD-1/PD-L1 Immune Checkpoint Inhibitors

Computational approaches in immune-oncology therapies focus on using data-driven methods to identify potential immune targets and develop novel drug candidates. In particular, the search for PD-1/PD-L1 immune checkpoint inhibitors (ICIs) has enlivened the field, leveraging the use of cheminformatics and bioinformatics tools to analyze large datasets of molecules, gene expression and protein-protein interactions. Up to now, there is still an unmet clinical need for improved ICIs and reliable predictive biomarkers. In this review, we highlight the computational methodologies applied to discovering and developing PD-1/PD-L1 ICIs for improved cancer immunotherapies with a greater focus in the last five years. The use of computer-aided drug design structure- and ligand-based virtual screening processes, molecular docking, homology modeling and molecular dynamics simulations methodologies essential for successful drug discovery campaigns focusing on antibodies, peptides or small-molecule ICIs are addressed. A list of recent databases and web tools used in the context of cancer and immunotherapy has been compilated and made available, namely regarding a general scope, cancer and immunology. In summary, computational approaches have become valuable tools for discovering and developing ICIs. Despite significant progress, there is still a need for improved ICIs and biomarkers, and recent databases and web tools have been compiled to aid in this pursuit.

CAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer

Immune checkpoint inhibitors (ICIs) have completely changed the approach pertaining to tumor diagnostics and treatment. Similarly, immunotherapy has also provided much needed data about mutation, expression and prognosis, affording an unprecedented opportunity for discovering candidate drug targets and screening for immunotherapy-relevant biomarkers. Although existing web tools enable biologists to analyze the expression, mutation and prognostic data of tumors, they are currently unable to facilitate data mining and mechanism analyses specifically related to immunotherapy. Thus, we effectively developed our own web-based tool, called Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer (CAMOIP), in which we are able to successfully screen various prognostic markers and analyze the mechanisms involved in biomarker expression and function, as well as immunotherapy. The analyses include information relevant to survival analysis, expression analysis, mutational landscape analysis, immune infiltration analysis, immunogenicity analysis and pathway enrichment analysis. This comprehensive analysis of biomarkers for immunotherapy can be carried out by a click of CAMOIP, and the software should greatly encourage the further development of immunotherapy. CAMOIP provides invaluable evidence that bridges the information between the data of cancer genomics based on immunotherapy, providing comprehensive information to users and assisting in making the value of current ICI-treated data available to all users. CAMOIP is available at https://www.camoip.net.

Undergraduate laboratory series that employs a complete polymerase chain reaction-restriction fragment length polymorphism experiment for determination of a single nucleotide polymorphism in CYP2R1 gene

Nowadays, novel Biochemistry lab techniques are being introduced at a very fast pace in scientific research. This requires development of new labs for undergraduate Biochemistry courses to equip the students with up-to-date techniques. However, the time limit of Biochemistry labs for undergraduate students represents a major obstacle. This article presents a clear set of laboratory exercises designed to introduce students to the use of polymerase chain reaction-restriction-fragment length polymorphism (PCR-RFLP) as a means of detection of genetic variants. Three consecutive lab experiments have been designed for the undergraduate students to serve this purpose. The first session was performed in a computer lab (dry lab) where students were taught how to obtain a specific gene sequence, identify an exact single nucleotide polymorphism location, choose the target sequence for amplification, design specific primers for this particular sequence and choose the most suitable restriction enzyme from web tools. The second and third lab sessions were performed as wet labs where in the second lab session, students optimized PCR conditions and performed a successful PCR. The PCR products were kept for use in the third lab session where they utilized the selected restriction enzyme and carried out gel electrophoresis to determine the exact genotype.

Web tools to fight pandemics: the COVID-19 experience

The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis. Our focus was driven on tools drawing data from the fields of epidemiology, genomics, interactomics and pharmacology, in order to provide a meaningful depiction of the current state of the art of COVID-19 online resources.

Grape-RNA: A Database for the Collection, Evaluation, Treatment, and Data Sharing of Grape RNA-Seq Datasets

Since its inception, RNA sequencing (RNA-seq) has become the most effective way to study gene expression. After more than a decade of development, numerous RNA-seq datasets have been created, and the full utilization of these datasets has emerged as a major issue. In this study, we built a comprehensive database named Grape-RNA, which is focused on the collection, evaluation, treatment, and data sharing of grape RNA-seq datasets. This database contains 1529 RNA-seq samples, 112 microRNA samples from the public platform, and 485 RNA-seq in-house datasets sequenced by our lab. We classified these data into 25 conditions and provide the sample information, cleaned raw data, expression level, assembled unigenes, useful tools, and other relevant information to the users. Thus, this study provides data and tools that should be beneficial for researchers by allowing them to easily use the RNA-seq. The provided information can greatly contribute to grape breeding and genomic and biological research. This study may improve the usage of RNA-seq.

miRNAtools: Advanced Training Using the miRNA Web of Knowledge

Micro-RNAs (miRNAs) are small non-coding RNAs that act as negative regulators of the genomic output. Their intrinsic importance within cell biology and human disease is well known. Their mechanism of action based on the base pairing binding to their cognate targets have helped the development not only of many computer applications for the prediction of miRNA target recognition but also of specific applications for functional assessment and analysis. Learning about miRNA function requires practical training in the use of specific computer and web-based applications that are complementary to wet-lab studies. In order to guide the learning process about miRNAs, we have created miRNAtools (http://mirnatools.eu), a web repository of miRNA tools and tutorials. This article compiles tools with which miRNAs and their regulatory action can be analyzed and that function to collect and organize information dispersed on the web. The miRNAtools website contains a collection of tutorials that can be used by students and tutors engaged in advanced training courses. The tutorials engage in analyses of the functions of selected miRNAs, starting with their nomenclature and genomic localization and finishing with their involvement in specific cellular functions.

Scipion web tools: Easy to use cryo-EM image processing over the web

Macromolecular structural determination by Electron Microscopy under cryogenic conditions is revolutionizing the field of structural biology, interesting a large community of potential users. Still, the path from raw images to density maps is complex, and sophisticated image processing suites are required in this process, often demanding the installation and understanding of different software packages. Here, we present Scipion Web Tools, a web-based set of tools/workflows derived from the Scipion image processing framework, specially tailored to nonexpert users in need of very precise answers at several key stages of the structural elucidation process.

TomExpress, a unified tomato RNA-Seq platform for visualization of expression data, clustering and correlation networks

The TomExpress platform was developed to provide the tomato research community with a browser and integrated web tools for public RNA-Seq data visualization and data mining. To avoid major biases that can result from the use of different mapping and statistical processing methods, RNA-Seq raw sequence data available in public databases were mapped de novo on a unique tomato reference genome sequence and post-processed using the same pipeline with accurate parameters. Following the calculation of the number of counts per gene in each RNA-Seq sample, a communal global normalization method was applied to all expression values. This unifies the whole set of expression data and makes them comparable. A database was designed where each expression value is associated with corresponding experimental annotations. Sample details were manually curated to be easily understandable by biologists. To make the data easily searchable, a user-friendly web interface was developed that provides versatile data mining web tools via on-the-fly generation of output graphics, such as expression bar plots, comprehensive in planta representations and heatmaps of hierarchically clustered expression data. In addition, it allows for the identification of co-expressed genes and the visualization of correlation networks of co-regulated gene groups. TomExpress provides one of the most complete free resources of publicly available tomato RNA-Seq data, and allows for the immediate interrogation of transcriptional programs that regulate vegetative and reproductive development in tomato under diverse conditions. The design of the pipeline developed in this project enables easy updating of the database with newly published RNA-Seq data, thereby allowing for continuous enrichment of the resource.