In silico algorithm

Clinical genetics laboratories have recently adopted guidelines for the interpretation of sequence variants set by the American College of Medical Genetics (ACMG) and Association for Molecular Pathology (AMP). The use of in silico algorithms to predict whether amino acid substitutions result in human disease is inconsistent across clinical laboratories.

3p vioraclene 31-03-2024 3 2   Download

The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms.

12p vialfrednobel 29-01-2022 6 0   Download

The consensus on how to choose a reference gene for serum or plasma miRNA expression qPCR studies has not been reached and none of the potential candidates have yet been convincingly validated. We proposed a new in silico approach of finding a suitable reference for human, circulating miRNAs and identified a new set of endogenous reference miRNA based on miRNA profiling experiments from Gene Expression Omnibus.

15p vijeeni2711 24-07-2021 7 0   Download

An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation.

13p viwyoming2711 16-12-2020 12 3   Download

The locations of the TM segments inside the membrane proteins are the consequence of a cascade of several events: the localizing of the nascent chain to the membrane, its insertion through the translocon, and the conformation adopted to reach its stable state inside the lipid bilayer.

7p vikentucky2711 26-11-2020 10 3   Download

Simulation of populations with specified characteristics such as allele frequencies, linkage disequilibrium etc., is an integral component of many studies, including in-silico breeding optimization.

9p vikentucky2711 24-11-2020 10 1   Download

Drug-target networks are receiving a lot of attention in late years, given its relevance for pharmaceutical innovation and drug lead discovery. Different in silico approaches have been proposed for the identification of new drug-target interactions, many of which are based on kernel methods.

16p vioklahoma2711 19-11-2020 9 2   Download

Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation.

6p vioklahoma2711 19-11-2020 8 1   Download

Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation strategies provide ever-improving results via in silico metrics. However, even with these advances, the number of compounds successfully repositioned via computational screening remains low.

12p vicolorado2711 23-10-2020 14 1   Download

High-throughput sequencing can establish the functional capacity of a microbial community by cataloging the protein-coding sequences (CDS) present in the metagenome of the community. The relative performance of diferent computational methods for identifying CDS from whole-genome shotgun sequencing is not fully established.

13p vicolorado2711 22-10-2020 7 0   Download

Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity.

12p vibaku2711 22-07-2020 13 1   Download