scholarly journals Prioritizing 2nd order interactions via support vector ranking using sensitivity indices on time series Wnt measurements†

2016 ◽  
Author(s):  
shriprakash sinha
Keyword(s):  
Signaling Pathway ◽  
Expression Profiles ◽  
Higher Order ◽  
Support Vector ◽  
Ranking Algorithm ◽  
Time Investment ◽  
Sensitivity Indices ◽  
Wet Lab ◽  
The Individual ◽  
Over Time

AbstractIt is widely known that the sensitivity analysis plays a major role in computing the strength of the influence of involved factors in any phenomena under investigation. When applied to expression profiles of various intra/extracellular factors that form an integral part of a signaling pathway, the variance and density based analysis yields a range of sensitivity indices for individual as well as various combinations of factors. These combinations denote the higher order interactions among the involved factors, that might be of interest in the working mechanism of the pathway. For example, there are 19 types of WNTs and 10 FZDs with their 2ndorder combinations high enough and it is not possible to know which one to test first (except for those for which wet lab validations have been confirmed). But the effect of these combinations vary over time as measurements of fold changes and deviations in fold changes vary. In this work, after estimating the individual effects of factors for a higher order combination, the individual indices are considered as discriminative features. A combination, then is a multivariate feature set in higher order (>=2). With an excessively large number of factors involved in the pathway, it is difficult to search for important combinations in a wide search space over different orders. Exploiting the analogy of prioritizing webpages using ranking algorithms, for a particular order, a full set of combinations of interactions can then be prioritized based on these features using a powerful ranking algorithm via support vectors. Recording the changing rankings of the combinations over time points and durations, reveals how higher order interactions behave within the pathway and when and where an intervention might be necessary to influence the pathway. This could lead to development of time based therapeutic interventions. Based on a small dataset in time, we were able to generate the rankings of the 2ndorder combinations between WNTs and FZDs at different time snap shots and for different duration or time periods. Code has been made available on Google drive athttps://drive.google.com/folderview?id=0B7Kkv8wlhPU-V1Fkd1dMSTd5ak0&usp=sharingSignificanceThe search and wet lab testing of unknown biological hypotheses in the form of combinations of various intra/extracellular factors that are involved in a signaling pathway, costs a lot in terms of time, investment and energy. To reduce this cost of search in a vast combinatorial space, a pipeline has been developed that prioritises these list of combinations so that a biologist can narrow down their investigation. The pipeline uses kernel based sensitivity indices to capture the influence of the factors in a pathway and employs powerful support vector ranking algorithm. The generic workflow and future improvements are bound to cut down the cost for many wet lab experiments and reveal unknown/untested biological hypothesis.

scholarly journals Prioritizing 2nd and 3rd order interactions via support vector ranking using sensitivity indices on static Wnt measurements - Part A [work in progress]

2016 ◽  
Author(s):  
shriprakash sinha
Keyword(s):  
Time Series Data ◽  
Expression Profiles ◽  
Search Space ◽  
Higher Order ◽  
Series Data ◽  
Support Vector ◽  
Data Set ◽  
Sensitivity Indices ◽  
Number Of Factors ◽  
The Individual

It is widely known that the sensitivity analysis plays a major role in computing the strength of the influence of involved factors in any phenomena under investigation. When applied to expression profiles of various intra/extracellular factors that form an integral part of a signaling pathway, the variance and density based analysis yields a range of sensitivity indices for individual as well as various combinations of factors. These combinations denote the higher order interactions among the involved factors that might be of interest in the working mechanism of the pathway. For example, in a range of fourth order combinations among the various factors of the Wnt pathway, it would be easy to assess the influence of the destruction complex formed by APC, AXIN, CSKI and GSK3 interaction. In this work, after estimating the individual effects of factors for a higher order combination, the individual indices are considered as discriminative features. A combination, then is a multivariate feature set in higher order (>2). With an excessively large number of factors involved in the pathway, it is difficult to search for important combinations in a wide search space over different orders. Exploiting the analogy of prioritizing webpages using ranking algorithms, for a particular order, a full set of combinations of interactions can then be prioritized based on these features using a powerful ranking algorithm via support vectors. The computational ranking sheds light on unexplored combinations that can further be investigated using hypothesis testing based on wet lab experiments. Here, the basic framework and results obtained on 2nd and 3rd order interactions on a toy example data set is presented. Subsequent manuscripts will examine higher order interactions in detail. Part B of this work deals with the time series data.

scholarly journals Inchoative discovery of plausible (un)explored synergistic combinatorial biological hypotheses for static/time series Wnt measurements via ranking search engine : BioSearch Engine Design

2018 ◽  
Author(s):  
shriprakash sinha
Keyword(s):  
Search Engine ◽  
Expert Advice ◽  
Support Vector ◽  
Advice Literature ◽  
Time Investment ◽  
Sensitivity Indices ◽  
Engine Design ◽  
Wnt Inhibitor ◽  
Wet Lab ◽  
Time Buffer

BACKGROUND Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combination of factors that might be affecting the pathway under certain conditions. Currently, a major problem in biology is to cherry pick the combinations based on expert advice, literature survey or guesses for investigation. The search and wet lab testing of these combinations costs a lot in terms of time, investment and energy. In a recent development of the PORCN-WNT inhibitor ETC-1922159 for colorectal cancer, a list of down-regulated genes were recorded in a time buffer after the administration of the drug. The regulation of the genes were recorded individually but for a majority, it is still not known which higher (≥ 2) order combinations might be playing a greater role in the pathway. RESULTS The pipeline provides a prioritised list of important 2nd order combinations of a range of family of genes involved in the Wnt pathway. More specifically, it reveals the various unexplored FZD-WNT combinations that have been untested till now in the pathway. In relation to ETC-1922159 affected combinations, the down-regulation of LGR-RNF family after the drug treatment is evident in these rankings as it takes bottom priorities for LGR5-RNF43 combination. The LGR6-RNF43 takes higher ranking than LGR5-RNF43, indicating that it might not be playing a greater role as LGR5 during the Wnt enhancing signals. These rankings confirm the efficacy of the proposed search engine design. CONCLUSION A pipeline has been developed to prioritise an nth order combination of factors that affect a signaling pathway. It takes into account the sensitivity indices computed from variance based (SOBOL) and density-kernel based (HSIC) methods to estimate the influence of each factor or combination of factors. These are then fed as feature vectors into a powerful support vector ranking algorithm that produces a ranked list of the interactions/combinations.

scholarly journals Sensitivity analysis based ranking reveals unknown biological hypotheses for down regulated genes in time buffer during administration of PORCN-WNT inhibitor ETC-1922159 in CRC†

2017 ◽  
Author(s):  
Shriprakash Sinha
Keyword(s):  
Colorectal Cancer ◽  
Signaling Pathway ◽  
Search Engine ◽  
Higher Order ◽  
Expert Advice ◽  
Support Vector ◽  
Combinatorial Search ◽  
Wnt Inhibitor ◽  
Wet Lab ◽  
Time Buffer

In a recent development of the PORCN-WNT inhibitor ETC-1922159 for colorectal cancer, a list of down-regulated genes were recorded in a time buffer after the administration of the drug. The regulation of the genes were recorded individually but it is still not known which higher (≥ 2) order interactions might be playing a greater role after the administration of the drug. In order to reveal the priority of these higher order interactions among the down-regulated genes or the likely unknown biological hypotheses, a search engine was developed based on the sensitivity indices of the higher order interactions that were ranked using a support vector ranking algorithm and sorted. For example, LGR family (Wnt signal enhancer) is known to neutralize RNF43 (Wnt inhibitor). After the administration of ETC-1922159 it was found that using HSIC (and rbf, linear and laplace variants of kernel) the rankings of the interaction between LGR5-RNF43 were 61, 114 and 85 respectively. Rankings for LGR6-RNF43 were 1652, 939 and 805 respectively. The down-regulation of LGR family after the drug treatment is evident in these rankings as it takes bottom priorities for LGR5-RNF43 interaction. The LGR6-RNF43 takes higher ranking than LGR5-RNF43, indicating that it might not be playing a greater role as LGR5 during the Wnt enhancing signals. These rankings confirm the efficacy of the proposed search engine design. Conclusion: Prioritized unknown biological hypothesis form the basis of further wet lab tests with the aim to reduce the cost of (1) wet lab experiments (2) combinatorial search and (3) lower the testing time for biologist who search for influential interactions in a vast combinatorial search forest. From in silico perspective, a framework for a search engine now exists which can generate rankings for nth order interactions in Wnt signaling pathway, thus revealing unknown/untested/unexplored biological hypotheses and aiding in understanding the mechanism of the pathway. The generic nature of the design can be applied to any signaling pathway or phenomena under investigation where a prioritized order of interactions among the involved factors need to be investigated for deeper understanding. Future improvements of the design are bound to facilitate medical specialists/oncologists in their respective investigations.SignificanceRecent development of PORCN-WNT inhibitor enantiomer ETC-1922159 cancer drug show promise in suppressing some types of colorectal cancer. However, the search and wet lab testing of unknown/unexplored/untested biological hypotheses in the form of combinations of various intra/ extracellular factors/genes/proteins affected by ETC-1922159 is not known. Currently, a major problem in biology is to cherry pick the combinations based on expert advice, literature survey or guesses to investigate a particular combinatorial hypothesis. A search engine has be developed to reveal and prioritise these unknown/untested/unexplored combinations affected by the inhibitor. These ranked unknown biological hypotheses facilitate in narrowing down the investigation in a vast combinatorial search forest of ETC-1922159 affected synergistic-factors.

scholarly journals Inchoative Discovery of Plausible (Un)explored Synergistic Combinatorial Biological Hypotheses for Static/Time Series Wnt Measurements via Ranking Search Engine : BioSearch Engine Design

2018 ◽  
Author(s):  
Shriprakash Sinha
Keyword(s):  
Search Engine ◽  
Expert Advice ◽  
Support Vector ◽  
Advice Literature ◽  
Time Investment ◽  
Sensitivity Indices ◽  
Engine Design ◽  
Wnt Inhibitor ◽  
Wet Lab ◽  
Time Buffer

\textsc{Background} Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combination of factors that might be affecting the pathway under certain conditions. Currently, a major problem in biology is to cherry pick the combinations based on expert advice, literature survey or guesses for investigation. The search and wet lab testing of these combinations costs a lot in terms of time, investment and energy. In a recent development of the PORCN-WNT inhibitor ETC-1922159 for colorectal cancer, a list of down-regulated genes were recorded in a time buffer after the administration of the drug. The regulation of the genes were recorded individually but for a majority, it is still not known which higher ($\geq 2$) order combinations might be playing a greater role in the pathway. \textsc{Results} The pipeline provides a prioritised list of important $2^{nd}$ order combinations of a range of family of genes involved in the Wnt pathway. More specifically, it reveals the various unexplored FZD-WNT combinations that have been untested till now in the pathway. In relation to ETC-1922159 affected combinations, the down-regulation of LGR-RNF family after the drug treatment is evident in these rankings as it takes bottom priorities for LGR5-RNF43 combination. The LGR6-RNF43 takes higher ranking than LGR5-RNF43, indicating that it might not be playing a greater role as LGR5 during the Wnt enhancing signals. These rankings confirm the efficacy of the proposed search engine design. \textsc{Conclusion} A pipeline has been developed to prioritise an $n^{th}$ order combination of factors that affect a signaling pathway. It takes into account the sensitivity indices computed from variance based (SOBOL) and density-kernel based (HSIC) methods to estimate the influence of each factor or combination of factors. These are then fed as feature vectors into a powerful support vector ranking algorithm that produces a ranked list of the interactions/combinations.

scholarly journals Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - Part A

2015 ◽  
Author(s):  
shriprakash sinha
Keyword(s):  
Colorectal Cancer ◽  
Time Series ◽  
Sensitivity Analysis ◽  
Wnt Signaling ◽  
Signaling Pathway ◽  
Expression Profiles ◽  
Biological Knowledge ◽  
Prior Biological Knowledge ◽  
Sensitivity Indices ◽  
Higher Dimensional

AbstractEver since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues. This manuscript • explores the strength of contributing factors in the signaling pathway, • analyzes the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and • investigates the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices. The results show the advantage of using density based indices over variance based indices mainly due to the former’s employment of distance measures & the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis & representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs & reveal hidden biological information within colorectal cancer samples. Code has been made available at Google drive onhttps://drive.google.com/folderview?id=0B7Kkv8wlhPU-Q2NBZGt1ZERrSVE&usp=sharing

On the Individual

1999 ◽  
Vol 4 (4) ◽  
pp. 205-218 ◽  
Author(s):  
David Magnusson
Keyword(s):  
School Psychologist ◽  
Real Life ◽  
Psychological Research ◽  
Developmental Research ◽  
Future Directions ◽  
The 1950S ◽  
The Individual ◽  
Over Time

A description of two cases from my time as a school psychologist in the middle of the 1950s forms the background to the following question: Has anything important happened since then in psychological research to help us to a better understanding of how and why individuals think, feel, act, and react as they do in real life and how they develop over time? The studies serve as a background for some general propositions about the nature of the phenomena that concerns us in developmental research, for a summary description of the developments in psychological research over the last 40 years as I see them, and for some suggestions about future directions.

Geographical aspects of the diffusion of passive houses

2013 ◽  
Vol 4 (2) ◽  
pp. 151-156 ◽  
Author(s):  
G. Kozma ◽  
E. Molnár ◽  
K. Czimre ◽  
J. Pénzes
Keyword(s):  
Energy Consumption ◽  
Energy Resources ◽  
Substantial Part ◽  
Renewable Energy Resources ◽  
Passive House ◽  
The Earth ◽  
Passive Houses ◽  
The Individual ◽  
Geographical Locations ◽  
Over Time

Abstract In our days, energy issues belong to the most important problems facing the Earth and the solution may be expected partly from decreasing the amount of the energy used and partly from the increased utilisation of renewable energy resources. A substantial part of energy consumption is related to buildings and includes, inter alia, the use for cooling/heating, lighting and cooking purposes. In the view of the above, special attention has been paid to minimising the energy consumption of buildings since the late 1980s. Within the framework of that, the passive house was created, a building in which the thermal comfort can be achieved solely by postheating or postcooling of the fresh air mass without a need for recirculated air. The aim of the paper is to study the changes in the construction of passive houses over time. In addition, the differences between the geographical locations and the observable peculiarities with regard to the individual building types are also presented.

Personality change and environmental concerns

2020 ◽  
Author(s):  
Christopher James Hopwood ◽  
Ted Schwaba ◽  
Wiebke Bleidorn
Keyword(s):  
Personality Traits ◽  
Personality Change ◽  
Environmental Concerns ◽  
Big Five Personality ◽  
German Population ◽  
Individual Level ◽  
Sustainable Behavior ◽  
Nationally Representative ◽  
The Individual ◽  
Over Time

Personal concerns about climate change and the environment are a powerful motivator of sustainable behavior. People’s level of concern varies as a function of a variety of social and individual factors. Using data from 58,748 participants from a nationally representative German sample, we tested preregistered hypotheses about factors that impact concerns about the environment over time. We found that environmental concerns increased modestly from 2009-2017 in the German population. However, individuals in middle adulthood tended to be more concerned and showed more consistent increases in concern over time than younger or older people. Consistent with previous research, Big Five personality traits were correlated with environmental concerns. We present novel evidence that increases in concern were related to increases in the personality traits neuroticism and openness to experience. Indeed, changes in openness explained roughly 50% of the variance in changes in environmental concerns. These findings highlight the importance of understanding the individual level factors associated with changes in environmental concerns over time, towards the promotion of more sustainable behavior at the individual level.

Associations Between Higher-Order Values Vary with Age, Education, and Income

2020 ◽  
Author(s):  
Maksim Rudnev
Keyword(s):  
Cognitive Abilities ◽  
Developed Countries ◽  
European Social Survey ◽  
Higher Order ◽  
Group Differences ◽  
Social Survey ◽  
Value Structures ◽  
Younger Age ◽  
The Individual ◽  
Representative Samples

A theory of basic human values relies on the similarity of value structures across countries. It has been well established that the quasi-circumplex value structure as a whole is indeed universal. However, less attention has been paid to the associations between specific values. This study investigated associations between four higher-order values across age, education, and income groups. We analyzed the data from national representative samples collected in 29 countries as part of the fourth round of the European Social Survey with a series of multilevel regressions. Younger age, higher levels of education and income coincided with higher independence of the four adjacent higher-order values, whereas among older, less educated, and less wealthy groups, values tended to merge into a single dimension of Social versus Person Focus. These differences were slightly weaker in more economically developed countries. The group differences in value associations may follow from corresponding differences in the degree of societal and individual empowerment, cognitive abilities, and socialization experiences. Accounting for the individual differences in relations between values may bring deeper understanding and higher predictive power to the studies of links between values and various behaviors or attitudes. , value structure, value interactions, European Social Survey

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

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