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Bandana Kumari

dblp:242/6976 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-5306-6666ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › proteomics
post-translational modification
0.412019
Identifying residues that determine palmitoylation using association rule mining · Bioinform. 2019
Bioinformatics and computational biology
protein function prediction
0.412019
Identifying residues that determine palmitoylation using association rule mining · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

association rule mining · 0.4
YearPublicationVenuePosition
2021 Identification of chloroplast and sub-chloroplast proteins from sequence-attributed features using support vector machine and domain information
abstract
Chloroplasts are one of the most important organelles of plants including algae. A number of vital biological pathways in them are exclusively confined to the chloroplast, thus, indicating the significance of chloroplastidic proteins. Hence, prediction of chloroplastidic proteins and their localization within the chloroplast (sub-chloroplastidial localization) can be of paramount importance in understanding the role of both novel and known chloroplastidic proteins. Several experimental methods have been developed to determine the subcellular localization of proteins; however, annotation of every protein using the experimental methods requires a lot of time and resources. To overcome these shortcomings of experimental approaches many computational methods have been proposed which minimize the amount of time and resources required. In pursuit of speeding up the prediction of chloroplastidic proteins and their sub-chloroplastidial localization besides maintaining efficiency, we developed Pfam domain and support vector machine based two level prediction frameworks, namely, SubChloroPred. At first level, SubChloroPred predicts the chloroplastidic proteins and at second level, their localization at sub-chloroplastidic locations such as thylakoid and stroma would be predicted. SubChloroPred has overall prediction accuracy of 94.86% at the first level and accuracies of 75.91% and 74.26% at the second level in thylakoid and stroma respectively. We have also developed a freely accessible webserver as well as standalone software for the use of scientific community, which can be accessed from the link http://proteininformatics.org/mkumar/SubChloroPred.
Anjali Garg, Bandana Kumari, Manish Kumar 0005, Equal Contribution
CIBCB3
2019 Identifying residues that determine palmitoylation using association rule mining
abstract
MOTIVATION: In eukaryotes, palmitoylation drives several essential cellular mechanisms like protein sorting, protein stability and protein-protein interaction. Several amino acids namely Cys, Gly, Ser, Thr and Lys undergo palmitoylation. But very little is known about the amino acid patterns that promote palmitoylation. RESULTS: We deduced presence of statistically significant amino acids around palmitoylation sites and their association with different palmitoylated residues i.e. Cys, Gly and Ser. The results suggest that palmitoylation, irrespective of its target residue, generally occurs at sites where Cys, Leu, Lys, Arg, Ser and Met are abundant. Furthermore, functional properties of the three types of palmitoylated proteins were compared. We observed similar functional behavior of Cys and Gly palmitoylated proteins but proteins with Ser palmitoylation showed distinctiveness from remaining two. Motif-wise functional conservation was also observed in Cys palmitoylated proteins. We also did functional annotation of predicted human palmitoylome. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Bandana Kumari, Manish Kumar 0005
Bioinform.1