Results 111 to 120 of about 526,558 (303)

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

open access: yesMolecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim   +3 more
wiley   +1 more source

An Algorithm for Template-Based Prediction of Secondary Structures of Individual RNA Sequences

open access: yesFrontiers in Genetics, 2017
While understanding the structure of RNA molecules is vital for deciphering their functions, determining RNA structures experimentally is exceptionally hard.
Josef Pánek   +2 more
doaj   +1 more source

The tree alignment model : algorithms, implementations and applications for the analysis of RNA secondary structures

open access: yes, 2005
Höchsmann M. The tree alignment model : algorithms, implementations and applications for the analysis of RNA secondary structures. Bielefeld (Germany): Bielefeld University; 2005.Phylogenetic analysis of nucleotide sequences and amino acid sequences has ...
Höchsmann, Matthias
core  

ZW4864‐mediated inhibition of the β‐catenin/BCL9/BCL9L complex reveals therapeutic potential in bladder cancer

open access: yesMolecular Oncology, EarlyView.
BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi   +11 more
wiley   +1 more source

Synchronous visual analysis and editing of RNA sequence and secondary structure alignments using 4SALE

open access: yesBMC Research Notes, 2008
Background The function of a noncoding RNA sequence is mainly determined by its secondary structure and therefore a family of noncoding RNA sequences is much more conserved on the structural level than on the sequence level. Understanding the function of
Dandekar Thomas   +3 more
doaj   +1 more source

Versatile and declarative dynamic programming using pair algebras

open access: yes, 2005
Steffen P, Giegerich R. Versatile and declarative dynamic programming using pair algebras. BMC Bioinformatics. 2005;6(1): 224.Background: Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of
Peter Steffen   +5 more
core   +1 more source

PARP inhibitors induce a senescence phenotype in non‐small cell lung carcinoma cell lines

open access: yesFEBS Open Bio, EarlyView.
Talazoparib is the most potent inducer of senescence among different PARP1 inhibitors in human NSCLC cells. In the absence of PARP, no senescence phenotype was observed, demonstrating that PARP1 is necessary for the induction of senescence by this inhibitor.
Camille Huart   +7 more
wiley   +1 more source

THE SECONDARY STRUCTURE OF COMPLEMENTARY RNA [PDF]

open access: yesProceedings of the National Academy of Sciences, 1962
E P, GEIDUSCHEK, J W, MOOHR, S B, WEISS
openaire   +2 more sources

RNA secondary structure and compensatory evolution.

open access: yesGenes & Genetic Systems, 1999
The classic concept of epistatic fitness interactions between genes has been extended to study interactions within gene regions, especially between nucleotides that are important in maintaining pre-mRNA/mRNA secondary structures. It is shown that the majority of linkage disequilibria found within the Drosophila Adh gene are likely to be caused by ...
Chen, Y.   +6 more
openaire   +4 more sources

RNA secondary structure prediction with Convolutional Neural Networks

open access: yes, 2023
reservedPredire il secondario, i.e. struttura di base-accoppiamento di un filamento di RNA piegato è un problema importante nella biologia sintetica e computazionale. Primo principio algoritmico approcci a questo compito sono difficili perché i modelli
BALDASSAR, DAVIDE
core  

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