Over the past decade, experimental and computational approaches for deep molecular and cellular profiling have become readily available and widely used in systems immunology and cancer systems biology. These include genomic, epigenomic, transcriptomic, proteomic, metabolomic, antibody-omic and cellular phenotypic datasets. The broad focus of this issue is on technologies that can be used to generate and interrogate combinations of these datasets in a principled fashion to uncover phenotypes and mechanisms underlying immunological disorders and cancer.
We are interested in manuscripts describing computational and high-throughput experimental techniques including novel devices that can be used to generate and/or analyze these multi-omic datasets. Of special interest are manuscripts that describe high-throughput, sample-sparing experimental approaches such as using microfluidic devices or other micro-/nano-scale technologies and integrative computational-experimental approaches. A major emphasis of the issue will also be advances in single-cell technologies (e.g., scRNA-seq, scATAC-seq) either on the computational and/or experimental fronts.
Manuscripts do not necessarily need to include both aspects; studies describing either novel computational approaches for the analyses of multi-omic datasets or creative experimental techniques for generating one or more of these datasets are welcome. However, manuscripts simply describing computational methods without demonstrating their applications on real-world datasets will not be considered a good fit for this issue.
Over the past decade, experimental and computational approaches for deep molecular and cellular profiling have become readily available and widely used in systems immunology and cancer systems biology. These include genomic, epigenomic, transcriptomic, proteomic, metabolomic, antibody-omic and cellular phenotypic datasets. The broad focus of this issue is on technologies that can be used to generate and interrogate combinations of these datasets in a principled fashion to uncover phenotypes and mechanisms underlying immunological disorders and cancer.
We are interested in manuscripts describing computational and high-throughput experimental techniques including novel devices that can be used to generate and/or analyze these multi-omic datasets. Of special interest are manuscripts that describe high-throughput, sample-sparing experimental approaches such as using microfluidic devices or other micro-/nano-scale technologies and integrative computational-experimental approaches. A major emphasis of the issue will also be advances in single-cell technologies (e.g., scRNA-seq, scATAC-seq) either on the computational and/or experimental fronts.
Manuscripts do not necessarily need to include both aspects; studies describing either novel computational approaches for the analyses of multi-omic datasets or creative experimental techniques for generating one or more of these datasets are welcome. However, manuscripts simply describing computational methods without demonstrating their applications on real-world datasets will not be considered a good fit for this issue.
