Results 81 to 90 of about 10,995,303 (306)

Versatile and declarative dynamic programming using pair algebras [PDF]

, 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, Steffen Peter, Robert Giegerich, Giegerich, Robert, Giegerich Robert, Steffen, Peter   +5 more
core   +1 more source

Promoter RNA secondary structure prediction.

, 2023
The secondary structure of SNV L 5 1–18 RNA (5‘-UAGUAGUAGACUCCGAGA-3‘) was carried out with RNAstructure [24]. (TIFF)
Quentin Durieux Trouilleton (16792991), Emmanuelle R. J. Quemin (16792997), Hélène Malet (14419624), Jan Kosinski (16589), Dominik Vogel (4026014), Dingquan Yu (16792994), Stephen Cusack (134664), Kay Grünewald (191757), Maria Rosenthal (2830790), Sigurdur R. Thorkelsson (16792988), Kristina Meier (16792985)   +10 more
core   +1 more source

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

A predictive model for secondary RNA structure using graph theory and a neural network

BMC Bioinformatics, 2010
Background Determining the secondary structure of RNA from the primary structure is a challenging computational problem. A number of algorithms have been developed to predict the secondary structure from the primary structure.
Knisley Jeff, Knisley Debra J, Koessler Denise R, Haynes Teresa   +3 more
doaj   +1 more source

Deep Learning in RNA Structure Studies

Frontiers in Molecular Biosciences, 2022
Deep learning, or artificial neural networks, is a type of machine learning algorithm that can decipher underlying relationships from large volumes of data and has been successfully applied to solve structural biology questions, such as RNA structure ...
Haopeng Yu, Yiman Qi, Yiliang Ding
doaj   +1 more source

High-resolution NMR structure of an RNA model system : the 14-mer cUUCGg tetraloop hairpin RNA [PDF]

, 2010
We present a high-resolution nuclear magnetic resonance (NMR) solution structure of a 14-mer RNA hairpin capped by cUUCGg tetraloop. This short and very stable RNA presents an important model system for the study of RNA structure and dynamics using NMR ...
Nozinovic, Senada, Fürtig, Boris, Jonker, Hendrik R. A., Schwalbe, Harald (Prof. Dr.), Richter, Christian   +4 more
core   +1 more source

Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling

, 2022
MOTIVATION: Recently, AlphaFold2 achieved high experimental accuracy for the majority of proteins in Critical Assessment of Structure Prediction (CASP 14).
Singh, Jaspreet, Zhou, Yaoqi, Litfin, Thomas, Paliwal, Kuldip, Singh, Jaswinder, Jaswinder Singh, Thomas Litfin, Jaspreet Singh, Yaoqi Zhou, Kuldip Paliwal   +9 more
core   +1 more source

Inhibition of cyclin‐dependent kinases 12/13 using CT7439 as a treatment for colorectal cancer with CDK12 upregulation

Molecular Oncology, EarlyView.
The proposed mechanism of action for the CDK12/13 inhibitor and cyclin K degrader, CT7439. CDK12/13 inhibition interrupts transcription elongation, leading to increased DNA damage that results in cell death. This agent is a potentially novel treatment option for patients with colorectal cancer. Created in BioRender. Cyclin‐dependent kinase (CDK) 12 and
Wylie K. Watlington, Divya L. Dayanidhi, Mohammad Zokaasadi, John B. Mantyh, Pelumi D. Olawuni, Gabrielle Rupprecht, Jeremy M. Force, Shannon McCall, Ashwani K. Bahl, David S. Hsu, Jason A. Somarelli   +10 more
wiley   +1 more source

Somatostatin receptor 4 (SSTR4) is a tumor suppressor in cutaneous and head & neck squamous cell carcinomas

Molecular Oncology, EarlyView.
This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi, Tuan Khang Huynh, Adway Kadam, Zahra Kardan, Yue Yan, Amina Jamal Laham, Sampath Kumar Loganathan   +6 more
wiley   +1 more source

RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning [PDF]

, 2019
The majority of our human genome transcribes into noncoding RNAs with unknown structures and functions. Obtaining functional clues for noncoding RNAs requires accurate base-pairing or secondary-structure prediction.
Zhou, Yaoqi, Hanson, Jack, Paliwal, Kuldip, Singh, Jaswinder   +3 more
core   +1 more source