Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data is a research paper published in Bioinformatics (2023). On theSindex it has a DataRank of 0.573. It has been cited 10 times, with 8 citing works in its 1-hop citation network.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.360
From this paper's citation signal
Citation Network Contribution
0.214
From 5 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 8 citers.
National Science Foundation
Grant: 1159943
Design of conformation-specific antibodies against unfolded and misfolded proteins
National Science Foundation
Grant: 1605266
National Science Foundation
Grant: 1813963
GOALI: Methods for designing antibodies specific for intrinsically disordered proteins
NIGMS NIH HHS
Grant: R35 GM136300
NIA NIH HHS
Grant: RF1 AG059723
National Institutes of Health
Grant: 5R35GM136300-04
Structure-guided antibody targeting of pre-selected epitopes in amyloidogenic aggregates
National Institutes of Health
Grant: 3RF1AG059723-01S1
Design and Evolution of Polyvalent Domain Antibodies Specific for Tau Aggregates
National Institutes of Health
Grant: 5R01AG080016-02
CD98hc Brain Shuttles for Delivering Off-the-shelf Neuroprotective Antibodies in Alzheimer's Disease
National Institutes of Health
Albert M. Mattocks Chair
Graduate Research Fellowship
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