scholarly journals KNIME-based Analysis of Off-Target Effect of Drugs Related to The Molecular 2D Fingerprint

2021 ◽  
Vol 24 ◽  
pp. 256-266
Author(s):  
Nihayatul Karimah ◽  
Gijs Schaftenaar
Keyword(s):  
Adverse Effects ◽  
Statistical Significance ◽  
Similarity Searching ◽  
Expectation Value ◽  
Open Source Data ◽  
Source Data ◽  
Similarity Ensemble Approach ◽  
Target Effect ◽  
Target Effects

Purpose: Structurally similar molecules are likely to have similar biological activity. In this study, similarity searching based on molecular 2D fingerprint was performed to analyze off-target effects of drugs. The purpose of this study is to determine the correlation between the adverse effects and drug off-targets. Methods: A workflow was built using KNIME to run dataset preparation of twenty-nine targets from ChEMBL, generate molecular 2D fingerprints of the ligands, calculate the similarity between ligand sets, and compute the statistical significance using similarity ensemble approach (SEA). Tanimoto coefficients (Tc) are used as a measure of chemical similarity in which the values between 0.2 and 0.4 are the most common for the majority of ligand pairs and considered to be insignificant similar. Result: The majority of ligand sets are unrelated, as is evidenced by the intrinsic chemical differences and the classification of statistical significance based on expectation value. The rank-ordered expectation value of inter-target similarity showed a correlation with off-target effects of the known drugs. Conclusion: Similarity-searching using molecular 2D fingerprint can be applied to predict off-targets and correlate them to the adverse effects of the drugs. KNIME as an open-source data analytic platform is applicable to build a workflow for data mining of ChEMBL database and generating SEA statistical model.

scholarly journals One-Class Classification of Natural Vegetation Using Remote Sensing: A Review

2021 ◽  
Vol 13 (10) ◽  
pp. 1892
Author(s):  
Sébastien Rapinel ◽  
Laurence Hubert-Moy
Keyword(s):  
Remote Sensing ◽  
Natural Vegetation ◽  
Open Source Data ◽  
Source Data ◽  
Good Classification ◽  
Long Term Monitoring ◽  
One Class Classification ◽  
Term Monitoring

Advances in remote sensing (RS) technology in recent years have increased the interest in including RS data into one-class classifiers (OCCs). However, this integration is complex given the interdisciplinary issues involved. In this context, this review highlights the advances and current challenges in integrating RS data into OCCs to map vegetation classes. A systematic review was performed for the period 2013–2020. A total of 136 articles were analyzed based on 11 topics and 30 attributes that address the ecological issues, properties of RS data, and the tools and parameters used to classify natural vegetation. The results highlight several advances in the use of RS data in OCCs: (i) mapping of potential and actual vegetation areas, (ii) long-term monitoring of vegetation classes, (iii) generation of multiple ecological variables, (iv) availability of open-source data, (v) reduction in plotting effort, and (vi) quantification of over-detection. Recommendations related to interdisciplinary issues were also suggested: (i) increasing the visibility and use of available RS variables, (ii) following good classification practices, (iii) bridging the gap between spatial resolution and site extent, and (iv) classifying plant communities.

Personality Traits-Based Terrorism Risk Assessment: Determining Reliability Using Open-Source Data

2021 ◽  
Author(s):  
Maike Knoechelmann ◽  
Garth Davies ◽  
Logan Macnair
Keyword(s):  
Risk Assessment ◽  
Open Source ◽  
Personality Trait ◽  
Statistical Significance ◽  
Instrument Validation ◽  
Threat Assessment ◽  
Terrorism Risk ◽  
Open Source Data ◽  
Source Data ◽  
Source Sample

Prominent terrorism case studies of individuals such as Omar Mateen, Dylann Roof, and Mohammed Merah indicate the need for personality trait-based terrorism risk assessment/threat assessment (TR/TA). This chapter provides an overview of Corrado’s, personality-based TR/TA instrument (see Chapter 14) by explaining the origin of each domain and the purpose of inclusion. Furthermore, this chapter displays results from a preliminary instrument validation study conducted on an open-source sample of 158 terrorists. Results of this study suggest strong statistical significance for many of the domains. This suggests the need for future inclusion of personality-based indicators in terrorism risk assessment.

scholarly journals How to draw the line – Raman spectroscopy as a tool for the assessment of biomedicines

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Christel Kamp ◽  
Björn Becker ◽  
Walter Matheis ◽  
Volker Öppling ◽  
Isabelle Bekeredjian-Ding
Keyword(s):  
Raman Spectroscopy ◽  
Proof Of Concept ◽  
Multiple Components ◽  
Open Source Data ◽  
Source Data ◽  
Batch Testing ◽  
Experimental Protocols ◽  
Analysis Platform ◽  
The Impact

Abstract Biomedicines are complex biochemical formulations with multiple components that require extensive quality control during manufacturing and in subsequent batch testing. A proof-of-concept study has shown that an application of Raman spectroscopy can be beneficial for a classification of vaccines. However, the complexity of biomedicines introduces new challenges to spectroscopic methodology that require advanced experimental protocols. We further show the impact of analytical protocols on vaccine classification using R as an Open Source data analysis platform. In conclusion, we advocate for standardized and transparent experimental and analytical procedures and discuss current findings and open challenges.

scholarly journals Defect CFT techniques in the 6d $$ \mathcal{N} $$ = (2, 0) theory

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Nadav Drukker ◽  
Malte Probst ◽  
Maxime Trépanier
Keyword(s):  
Stress Tensor ◽  
Unitary Representations ◽  
Point Function ◽  
Displacement Operator ◽  
Expectation Value ◽  
Operator Expansion ◽  
Bulk Stress ◽  
Defect Operator ◽  
Tensor Multiplet

Abstract Surface operators are among the most important observables of the 6d $$ \mathcal{N} $$ N = (2, 0) theory. Here we apply the tools of defect CFT to study local operator insertions into the 1/2-BPS plane. We first relate the 2-point function of the displacement operator to the expectation value of the bulk stress tensor and translate this relation into a constraint on the anomaly coefficients associated with the defect. Secondly, we study the defect operator expansion of the stress tensor multiplet and identify several new operators of the defect CFT. Technical results derived along the way include the explicit supersymmetry tranformations of the stress tensor multiplet and the classification of unitary representations of the superconformal algebra preserved by the defect.

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