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View article: PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization
PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization Open
Single-cell perturbation (scPerturbation) sequencing techniques, represented by single-cell genetic perturbation (e.g. Perturb-seq) and single-cell chemical perturbation (e.g. sci-Plex), result from the integration of single-cell toolkits …
View article: PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization
PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization Open
Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic perturbation sequencing (e.g., Perturb-seq) and single cell chemical perturbation sequencing (e.g., sci-Plex), result from the integration …
View article: Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond
Toward subtask decomposition-based learning and benchmarking for genetic perturbation outcome prediction and beyond Open
Deciphering cellular responses to genetic perturbations is fundamental for a wide array of biomedical applications, ranging from uncovering gene roles and interactions to unraveling effective therapeutics. Accurately predicting the transcr…
View article: DrSim: Similarity Learning for Transcriptional Phenotypic Drug Discovery
DrSim: Similarity Learning for Transcriptional Phenotypic Drug Discovery Open
Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as connectivity map (CMap) and library of integrated network-based cellular signatures (LINCS), have been pr…
View article: Dr. Sim: Similarity Learning for Transcriptional Phenotypic Drug discovery
Dr. Sim: Similarity Learning for Transcriptional Phenotypic Drug discovery Open
Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as Connectivity Map (CMap) and Library of Integrated Network-Based Cellular Signatures (LINCS), have been pr…
View article: The tumor therapy landscape of synthetic lethality
The tumor therapy landscape of synthetic lethality Open
Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop the Synthetic Lethality Knowledge Graph (SLKG)…
View article: Systematically Characterizing A-to-I RNA Editing Neoantigens in Cancer
Systematically Characterizing A-to-I RNA Editing Neoantigens in Cancer Open
A-to-I RNA editing can contribute to the transcriptomic and proteomic diversity of many diseases including cancer. It has been reported that peptides generated from RNA editing could be naturally presented by human leukocyte antigen (HLA) …
View article: iDMer: an integrative and mechanism-driven response system for identifying compound interventions for sudden virus outbreak
iDMer: an integrative and mechanism-driven response system for identifying compound interventions for sudden virus outbreak Open
Emerging viral infections seriously threaten human health globally. Several challenges exist in identifying effective compounds against viral infections: (1) at the initial stage of a new virus outbreak, little information, except for its …
View article: ASNEO: Identification of personalized alternative splicing based neoantigens with RNA-seq
ASNEO: Identification of personalized alternative splicing based neoantigens with RNA-seq Open
Cancer neoantigens have shown great potential in immunotherapy, while current software focuses on identifying neoantigens which are derived from SNVs, indels or gene fusions. Alternative splicing widely occurs in tumor samples and it has b…
View article: pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Background Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid ident…
View article: The Landscape of Tumor Fusion Neoantigens: A Pan-Cancer Analysis
The Landscape of Tumor Fusion Neoantigens: A Pan-Cancer Analysis Open
Compared with SNV&indel-based neoantigens, fusion-based neoantigens are not well characterized. In the present study, we performed a comprehensive analysis of the landscape of tumor fusion neoantigens in cancer and proposed a score scheme …
View article: MOESM10 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM10 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 10: Table S9. A. Clinical information and neoantigen information of cohort Rizvi (n=31). B. Clinical information and neoantigen information of cohort Snyder (n=59). C. Clinical information and neoantigen information of coho…
View article: MOESM11 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM11 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 11: Table S10. A. Candidate neoepitopes information obtained from patient CA9903 in Rizvi cohort using pTuneos Pre&RecNeo. B. Candidate neoepitopes information obtained from patient CR9306 in Snyder cohort using pTuneos Pre…
View article: MOESM4 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM4 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 4: Table S3. A. Clinical information and neoantigen information of stage III/IV stomach adenocarcinoma (n=166). B. Clinical information and neoantigen information of stage III/IV lung adenocarcinoma (n=101). C. Clinical inf…
View article: MOESM2 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM2 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 2: Table S1. Descriptions of training data used in pTuneos Pre&RecNeo.
View article: MOESM6 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM6 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 6: Table S5. A. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_21. B. Candidate neoepitopes identified using pTuneos Pre&RecNeo from MEL_38. C. Candidate neoepitopes identified using pTuneos Pre&RecNeo f…
View article: MOESM7 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM7 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 7: Table S6. A. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_38. B. Refined neoepitope rank obtained by pTuneos RefinedNeo of MEL_218.
View article: MOESM5 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM5 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 5: Table S4. A list of 13-gene MHC II signature which associated with immune signature.
View article: MOESM8 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM8 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 8: Table S7. Experimentally confirmed immunogenic and non-immunogenic peptides in Zacharakis et al., Tran et al. and Gros et al.
View article: MOESM3 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM3 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 3: Table S2. Experimentally confirmed immunogenic and non-immunogenic peptides in melanoma from Carreno et al. (ref. [15]).
View article: MOESM9 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data
MOESM9 of pTuneos: prioritizing tumor neoantigens from next-generation sequencing data Open
Additional file 9: Table S8. A. Candidate neoepitopes identified using pTuneos from 7 samples in Zacharakis et al., Tran et al. and Gros et al. B. Candidate neoepitopes identified using MuPeXI from 7 samples in Zacharakis et al., Tran et a…
View article: Unexpected CRISPR off-target mutation pattern<i>in vivo</i>are not typically germline-like
Unexpected CRISPR off-target mutation pattern<i>in vivo</i>are not typically germline-like Open
To the Editor Schaefer et al. 1 (referred to as Study_1 ) recently presented the provocative conclusion that CRISPR-Cas9 nuclease can induce many unexpected off-target mutations across the genome that arise from the sites with poor homolog…