Is devoted to advancing scientific understanding of living systems through computation. The unit promotes and supports the adoption, use, and development of bioinformatics tools for advancing biological research. We organize and teach courses and workshops for all our services, as well train individually to use the various tools. Since bioinformatics is such a broad field, our efforts are focused on those topics that are most needed by Weizmann researchers.
The Bioinformatics Unit is supported by the Wertheimer Center for Computational Biology.
Support is available for complete analyses, and for teaching researchers/students how to analyze their results independently. We encourage researchers to consult us when planning a project.
Click on the analysis titles below for detailed information.
The advent of deep sequencing platforms has opened exciting new avenues to life science researchers. Our aim is to help you in experimental design and interpretation of the massive data generated by your scientific interests. Our current expertise is in the following applications: Transcriptome analysis: RNA-Seq, Mars-seq and single cell RNA-Seq (scRNA) and other multiome single cell analysis (scATAC-Seq, CITE-Seq etc.) as well as ChIP-Seq, small RNA-Seq, de novo assembly (RNA and DNA level) and genetic variation detection. We will be happy to extend our knowledge in this dynamic field, and provide analysis for additional application types.
Designing CRISPR guides for various types of analyses and checking the results.
This topic includes all of the classical bioinformatics problems, including troubleshooting Sanger sequencing, cloning design, primer design, database searches, multiple alignments, prediction of post-translational modifications, phylogenetic analysis and promoter analysis.
We provide biostatistical support at different stages of the experiment. Yet, we encourage researchers to consult a statistician early in the planning stage of a project, discussing aspects of experimental design, sample size calculations, organization of data, statistical analysis of the results, presentation and interpretation.
The usage of artificial intelligence manifests today almost in every field, and found to be a successful tool for many applications. We provide deep learning, machine learning and AI in numerous applications, such as: medical informatics - examining patients records in order to discover complex relations, genomics - recognizing functional patterns in data, proteomics prediction of protein folding, structure, and function, and more.
Microarray support starts from experimental design (kick-off meetings, in conjunction with the wet lab) before the biological experiment is performed, through the final analysis after the microarray has been run. Analysis includes pathways and Gene Ontology enrichment of gene lists.