Kuldip Paliwal
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Explore the profile of Kuldip Paliwal including associated specialties, affiliations and a list of published articles.
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Articles
33
Citations
1188
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Recent Articles
1.
Singh J, Paliwal K, Litfin T, Singh J, Zhou Y
Bioinformatics
. 2022 Jun;
38(16):3900-3910.
PMID: 35751593
Motivation: Recently, AlphaFold2 achieved high experimental accuracy for the majority of proteins in Critical Assessment of Structure Prediction (CASP 14). This raises the hope that one day, we may achieve...
2.
Singh J, Paliwal K, Litfin T, Singh J, Zhou Y
Sci Rep
. 2022 May;
12(1):7607.
PMID: 35534620
Protein language models have emerged as an alternative to multiple sequence alignment for enriching sequence information and improving downstream prediction tasks such as biophysical, structural, and functional properties. Here we...
3.
Solayman M, Litfin T, Singh J, Paliwal K, Zhou Y, Zhan J
Brief Bioinform
. 2022 Mar;
23(3).
PMID: 35348613
Characterizing RNA structures and functions have mostly been focused on 2D, secondary and 3D, tertiary structures. Recent advances in experimental and computational techniques for probing or predicting RNA solvent accessibility...
4.
Singh J, Litfin T, Singh J, Paliwal K, Zhou Y
Bioinformatics
. 2022 Feb;
38(7):1888-1894.
PMID: 35104320
Motivation: Accurate prediction of protein contact-map is essential for accurate protein structure and function prediction. As a result, many methods have been developed for protein contact map prediction. However, most...
5.
Singh J, Paliwal K, Singh J, Zhou Y
J Chem Inf Model
. 2021 May;
61(6):2610-2622.
PMID: 34037398
RNA three-dimensional structure prediction has been relied on using a predicted or experimentally determined secondary structure as a restraint to reduce the conformational sampling space. However, the secondary-structure restraints are...
6.
Zhang T, Singh J, Litfin T, Zhan J, Paliwal K, Zhou Y
Bioinformatics
. 2021 May;
37(20):3494-3500.
PMID: 34021744
Motivation: The accuracy of RNA secondary and tertiary structure prediction can be significantly improved by using structural restraints derived from evolutionary coupling or direct coupling analysis. Currently, these coupling analyses...
7.
Singh J, Litfin T, Paliwal K, Singh J, Hanumanthappa A, Zhou Y
Bioinformatics
. 2021 May;
37(20):3464-3472.
PMID: 33983382
Motivation: Knowing protein secondary and other one-dimensional structural properties are essential for accurate protein structure and function prediction. As a result, many methods have been developed for predicting these one-dimensional...
8.
Singh J, Paliwal K, Zhang T, Singh J, Litfin T, Zhou Y
Bioinformatics
. 2021 Mar;
37(17):2589-2600.
PMID: 33704363
Motivation: The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in particular) has transformed our perception about the roles of RNAs in living organisms. Our ability to understand them,...
9.
Hanumanthappa A, Singh J, Paliwal K, Singh J, Zhou Y
Bioinformatics
. 2020 Oct;
36(21):5169-5176.
PMID: 33106872
Motivation: RNA solvent accessibility, similar to protein solvent accessibility, reflects the structural regions that are accessible to solvents or other functional biomolecules, and plays an important role for structural and...
10.
Barik A, Katuwawala A, Hanson J, Paliwal K, Zhou Y, Kurgan L
J Mol Biol
. 2019 Dec;
432(11):3379-3387.
PMID: 31870849
Computational predictions of the intrinsic disorder and its functions are instrumental to facilitate annotation for the millions of unannotated proteins. However, access to these predictors is fragmented and requires substantial...