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1. A machine learning algorithm with subclonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity

4. Large-Scale Analysis of Kinase Signaling in Yeast Pseudohyphal Development Identifies Regulation of Ribonucleoprotein Granules.

5. The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response.

7. Supplementary Data from Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

8. Supplementary Table from Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

9. Data from Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

10. Supplementary Figure from Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

11. Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

12. Kir2.1 Interactome Mapping Uncovers PKP4 as a Modulator of the Kir2.1-Regulated Inward Rectifier Potassium Currents

13. RAD51AP1 regulates ALT-HDR through chromatin-directed homeostasis of TERRA

14. Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

15. 79 Extensively validated HLA LOH algorithm demonstrates an association between HLA LOH and genomic instability

16. Allele-specific RNA interference prevents neuropathy in Charcot-Marie-Tooth disease type 2D mouse models

17. Validated machine learning algorithm with sub-clonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity

18. 73 Orthogonally and functionally validated algorithm for detecting HLA loss of heterozygosity

19. Philosopher: a versatile toolkit for shotgun proteomics data analysis

20. PAF1 complex interactions with SETDB1 mediate promoter H3K9 methylation and transcriptional repression ofHoxa9andMeis1in acute myeloid leukemia

21. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics

22. Abstract 1898: Accurate modeling of antigen processing and MHC peptide presentation using large-scale immunopeptidomes and a novel machine learning framework

23. Abstract 2512: Pan-cancer characterization of the tumor and immune microenvironment facilitates identification of cancer-specific biological signatures

24. Abstract 2085: Precision neoantigen discovery using a pan-allelic machine learning model for enabling the development of composite biomarkers and personalized immunotherapy

25. Functions of the COPII gene paralogs SEC23A and SEC23B are interchangeable in vivo

26. Targeting the MLL complex in castration-resistant prostate cancer

27. Proteomic profiling of naïve multiple myeloma patient plasma cells identifies pathways associated with favourable response to bortezomib-based treatment regimens

28. HSC70 is a chaperone for wild-type and mutant cardiac myosin binding protein C

29. PAF1 complex interactions with SETDB1 mediate promoter H3K9 methylation and transcriptional repression of

30. The Function of the COPII Gene Paralogs SEC23A and SEC23B Are InterchangeableIn Vivo

31. Using MSFragger for ultrafast database searching

32. Genetic Networks Inducing Invasive Growth in Saccharomyces cerevisiae Identified Through Systematic Genome-Wide Overexpression

33. SAINT: probabilistic scoring of affinity purification–mass spectrometry data

34. Abstract 18826: Cardiac Myosin Binding Protein C Mutants Interact With and Cause Mislocalization of the Hsp70 Family Chaperones

35. The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response

36. Analyzing protein-protein interactions from affinity purification-mass spectrometry data with SAINT

37. Large-Scale Analysis of Kinase Signaling in Yeast Pseudohyphal Development Identifies Regulation of Ribonucleoprotein Granules

38. Thioredoxin domain containing 5 (TXNDC5) as a marker of response in multiple myeloma – validation studies of proteomic profiling

39. The CRAPome: a contaminant repository for affinity purification–mass spectrometry data

40. Proteomic Profiling of Multiple Myeloma (MM) Cells Using iTRAQ and Label-Free Quantitative Proteomics for the Prediction of Complete or near Complete Response (CR/nCR) In Frontline Treatment with Lenalidomide, Bortezomib, and Dexamethasone

41. Proteomic Signature Predicting Achievement of Very Good Partial Response In Patients with Multiple Myeloma Based On Complementary Label-Free and iTRAQ Quantitative Proteome Analysis

42. Proteomic Profiling of Multiple Myeloma Plasma Cells and Normal Plasma Cells Reveals Differential Expression of Clu1 and Basp1 Proteins

43. Proteomic Profiling of Multiple Myeloma Using iTRAQ Labeling Followed by Multidimensional Liquid Chromatography and Tandem Mass Spectrometry

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