Introduction to Silico Analysis

What is/are Silico Analysis?

Silico Analysis - Functional in silico analysis found that DNAMeFourLncSig-related mRNAs were mainly enriched in cell differentiation, tissue development and immune-related pathways. ^[1] Binding of FA to the mouse 5-HT1A receptor was evaluated by in silico analysis. ^[2] Previously in silico analysis of human PL scramblases, predicted the presence of an uncharacterized cholesterol-binding domain spanning partly in the transmembrane helix as well as in the adjacent extracellular coil. ^[3] In silico analysis provided an explanation for E484K immune evasion. ^[4] In silico analysis suggested that αKG binds to mouse OXGR1. ^[5] Here, we utilize in silico analysis combined with in␣vivo genetic and biochemical approaches to investigate the fermentative metabolism of glycerol in Escherichia coli. ^[6] The sequencing and in silico analysis of their genomes, and the characterisation of their technological and safety properties, confirmed their potential as starters. ^[7] 0 Affymetrix) and iii) signal pathways and pathophysiological processes in which differentially expressed genes are involved (in silico analysis by the IPA software, QIAGEN). ^[8] Our in silico analysis revealed 146 genes regulated by miR-31 in HNSCC cells. ^[9] The genetic determinants of the underlying mechanisms have all been found by in silico analysis of the genome. ^[10] In silico analysis and luciferase assay uncovered the probable regulatory role of the rs2289521 variant on expression. ^[11] Nuclear localization was supported by in-silico analysis of nuclear localization predicted scores of peptide sequences. ^[12] Seven substitutions at position V1 (E374) indicated its functional role in autoprocessing and catalytic activity further supported by in silico analysis showing vital interaction between residues 374 and 547 in creating proper autocatalytic environment. ^[13] (CQ) against human cervical adenocarcinoma HeLa cell line and in silico analysis of selected active agents against apoptosis executioner enzyme caspase-3. ^[14] CYP1B1 and MYOC genes were screened using Sanger sequencing with in-silico analysis of the variants using Polymorphism Phenotyping v. ^[15] In silico analysis identified 17 potential off-targets, of which only one was differentially expressed after GFP-i. ^[16] A comprehensive in-silico analysis (i. ^[17] A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. ^[18] In silico analysis by modelling tool ADMET and prediction of biological activity of these compounds further validated them as putative therapeutic molecules against SARS-CoV-2. ^[19] By applying in silico analysis, we have found two highly conserved GRHL2 binding sites in the 1st intron of the gene encoding S100A10 protein. ^[20] Methods In the present manuscript, an in silico analysis of the genetic variations in CA27. ^[21] The purpose of our in silico analysis is to point out that IVNDT motif of ZIKV E-GL region should be taken in consideration for the development of safe and effective anti-Zika vaccines by precluding the possibility of adverse neurologic events including autoimmune diseases such as GBS through a potent mimicry with Heat Shock 70 kDa protein 12A (HSP70 12A). ^[22] 001), in line with their expression levels in cancer tissue according to an in silico analysis. ^[23] Methodology: In this in silico analysis, Gene Expression Omnibus Dataset GDS5056 was used to shortlist 23 genes differentially up regulated and co-expressed along with Hes1 during adipocyte stem cell differentiation in obese patients. ^[24] Enzyme kinetics of two putative methemoglobin reductases with methemoglobins as substrates and in silico analysis support interaction between the hemoglobins and the two reduction partners as also observed in vitro. ^[25] The present studies were designed to synthesize the three disulfide derivatives bearing S-S bond formation, their characterization and explore the antibacterial activity using in silico analysis. ^[26] In silico analysis of the promoter region of SbLOXs identified different hormones responsive cis-elements. ^[27] In silico analysis of tumors from MITF-E318K melanoma carriers in the TCGA Pan-Cancer-Atlas dataset confirmed the association with BRAF mutation and 9p21. ^[28] OsWRKY transcriptional regulation was predicted by in silico analysis of cis-regulatory elements. ^[29] This paper presents a novel computational framework for the in silico analysis of rank-one multilayered electro-active polymer composites exhibiting complex deformation patterns. ^[30] The anti-calcific role of miR-132 was further corroborated by in silico analysis, luciferase assays in HEK293 cells, and transfecting APCs with miR-132 agomir and antagomir, followed by assessment of osteochondrogenic markers. ^[31] Correspondingly, in silico analysis indicates that plasminogen is recruitable by the viral neuraminidase for proteolytic activation due to the loss of a strongly conserved N-glycosylation site at position 130. ^[32] The ability to predict the transglycosylation activity of glycosidases by in silico analysis was investigated. ^[33] Here, we combined proteomics with in silico analysis to characterize the range of effects of DMB in vivo throughout the course of early postinfarction remodeling. ^[34] In silico analysis further pointed at transcription factors of GATA, DOF, WRKY types as putative regulators of 1-SST. ^[35] Pathogenicity of variants was predicted by in silico analysis. ^[36] Finally, in silico analysis was conducted to further evaluation of molecular function of the identified genetic variants. ^[37] Using in silico analysis on multiple GEO PCa datasets, we found low expression level of miR-132 was associated with poor clinical prognosis, transition from androgen dependent (AD) to independent (AI) stage and metastasis. ^[38] An in-silico analysis predicts that members of this group harbor a highly conserved and structured Myb-DBD and a large portion of intrinsically disordered residues. ^[39] In silico analysis were developed to evaluate the binding capacity of LDL-R to apolipoproteins B100 and E. ^[40] In silico analysis, we found that 8,466 primer pairs of 3,288 SSRs yielded one product (monomorphic) simultaneously in five Gossypium species. ^[41] We also performed in silico analysis to investigate Dact1 gene expression in human myopathies, and evaluated the Dact1 protein structure to seek an explanation for the accumulation of Dact1 protein aggregates in the nuclei of myogenic cells. ^[42] Novel Corona virus-2 (Covid-19) is spreading and causing major damage around the globe and constantly increasing daily There is a prerequisite of expeditious development of safe and efficient drugs for such a contagious disease In this regard, utilization of a computational approach with an aim to provide potential enzyme inhibitors derived from natural resources will give a providential therapy The present study investigated one of the promising plants namely Glycyrrhiza glabra L It has various medicinal properties viz anti-inflammatory, anti-cancer, anti-demulcent, expectorant, etc In-Silico Analysis of liquiritin against SARS-CoV-2 Mpro was carried out using Autodock 4 2 6 and results were compared with presently prescribed drugs i e dexamethasone, remdesivir, hydroxychloroquine, and azithromycin The binding energy of liquiritin was found to be -6 62 kcal/mol It shows presence of hydrogen bond, hydrophobic interaction and electrostatic interaction with six active residues THR26, GLY143, CYS145, HIS 164, GLU166, and GLN189 Comparative studies investigated that dexamethasone, remdesivir, hydroxychloroquine, and azithromycin have four (THR26, GLY143, CYS145, GLU166), three (CYS145, GLU166, GLN189), four (GLY143, CYS145, HIS 164, GLN189) and two (GLU166, GLN189) identical active residues, respectively The present study recommended liquiritin as a potential candidate against SARS-CoV-2 as it is naturally derived and has tremendous traditional usage against various diseases However, in-vitro and in-vivo studies are required to prove its efficacy. ^[43] In silico analysis of promoters of the genes indicated a possible link to transcription factors reported earlier to respond to viral titers in rice. ^[44] In vitro culturing of ILCs was used to validate findings from in silico analysis. ^[45] Transient transfections of Hmgcr-promoter mutants and in silico analysis suggest altered binding of Runx3 and Srebf1 across A-405G site. ^[46] In silico analysis of the genomic region delimited by the most significant 1BL markers (~8 Mb) identified a predicted gene encoding for a glycosyl transferase (GT) of the GT61 family which is likely a candidate gene associated with the observed AX variation. ^[47] The identification of the AMP sequences was performed by in silico analysis as well as by molecular cloning and nucleotide sequencing. ^[48] An in silico analysis confirmed that, even for strong noise, the classical model can be identified robustly. ^[49] In silico analysis of the putative target genes of these miRNAs showed associations of variants in several target genes with stroke. ^[50]

transcription factor binding

Via in silico analysis, we identified transcription factor binding sites that could potentially influence methylation-dependent gene transcription. ^[1] The in silico analysis revealed that the rs968697 polymorphism in the promoter region of the HMGA2 gene could influence transcription factor binding, including ATF6, DBP, CDPCR3, DR3, NRSF, PAX8, PPARA, SZF11, TAXCREB and POLR2A. ^[2] Using in silico analysis, we identified several candidate transcription factor binding sites. ^[3] Importantly, in silico analysis showed that the C/T transition at this locus gives rise to two new transcription factor binding sites (TFBS), E2F1 and Nkx3-2. ^[4] First, in silico analysis indicated that these two promoters both contain numerous putative transcription factor binding sites including NF-κB, CREB, and CREBP1, and both contain a TATA box. ^[5]

cis acting regulatory

Several essential core cis-acting elements and numerous light-responsive cis-acting regulatory elements were identified in Ppd-D1b promoter by the in-silico analysis. ^[1] In silico analysis showed that various development-associated, phytohormone-responsive, and stress-related cis-acting regulatory elements were enriched in the promoter regions of BnMYB-related genes. ^[2] In-silico analysis of cis-acting regulatory elements of BrAGL8-1, BrAGL42-1, BrNAC029-2, BrNAC092-1, and BrWRKY70-3 of B. ^[3] In silico analysis revealed the presence of different cis-acting regulatory elements related to growth, stress and hormonal responsiveness in the upstream region of CsJAZ genes. ^[4]

basic leucine zipper

Initially, we performed an in silico analysis to identify potential transcription binding sites for the basic leucine zipper 62 transcription factor (bZIP62 TF) in the target branching related genes. ^[1] Initially, we performed an in silico analysis to identify potential binding sites for the basic leucine zipper 62 transcription factor (AtbZIP62 TF) in the promoter of the target genes, and constructed their protein–protein interaction networks. ^[2] Both genes contain a DUF1118 protein domain, which has the molecular characteristics of a basic leucine zipper (bZIP) transcription factor, based on in silico analysis. ^[3]

absorption distribution metabolism

In silico analysis of the major active chemical constituents (Oroxylin A, Baicalein and Chrysin) of OIE indicated that OIE has a favorable absorption, distribution, metabolism and excretion (ADME) profile. ^[1] In addition, in silico analysis of these three biomolecules was performed to predict parameters of absorption, distribution, metabolism and excretion. ^[2] The results of molecular docking and in silico analysis of absorption, distribution, metabolism, excretion, and toxicity revealed that the chosen complexes agree with the Lipinski Rule and have appropriate pharmacokinetic features which could be used as templates for the development of novel anti-inflammatory agents with substantial anticancer activity. ^[3]

amino acid substitution

The R545H missense variant has been found at very low allelic frequency in public databases, and in silico analysis showed that this amino acid substitution is predicted to have a damaging role. ^[1] With the help of in-silico analysis of a hypothetical R-protein (Hyp-R) in sesame, we tested the hypothesis that how amino acid substitution in the conserved P-loop motif can affect the interaction between ligand and NB-ARC domain. ^[2] RESULTS In-silico analysis of the amino acid substitution within CERS2 caused by the rs267738 mutation suggested that rs267738 is deleterious for enzyme function. ^[3]

silico analysis revealed

Our in silico analysis revealed 146 genes regulated by miR-31 in HNSCC cells. ^[1] In silico analysis revealed that ‘gVirE2+ssDNA’ complex is structurally less stable than ‘VirE2+ ssDNA’ complex. ^[2] In silico analysis revealed that the fusion protein comprising IL-2 and sVEGFR-1 has stable structure and the selected linker can efficiently separate the two domains. ^[3] In-silico analysis revealed the target genes involved in the miR-21 and MMP9 interaction network. ^[4] In silico analysis revealed VraG contains a single 200-residue extracellular loop (EL) situated between the 7th and 8th transmembrane segments (out of 10). ^[5] In this study, in silico analysis revealed the existence of 10 cart paralogs, here named cart1a, 1b1, 1b2, 2a, 2b1, 2b2, 3a1, 3a2, 3b, and 4. ^[6] Although it was previously reported to share a high degree of homology with mammalian lymphotoxin (LT)-β, in silico analysis revealed that RB-TNFN differed slightly from mammalian LT-β in its genomic structure, phylogenetic relationship, and predicted protein tertiary structure, whereas the genomic location of TNFN (immediately behind TNF-α) was the same as that of LT-β. ^[7] The results of evolutionary conservation and in silico analysis revealed that the p. ^[8] In silico analysis revealed that seven of these variants are predicted to affect protein function. ^[9] In silico analysis revealed the satisfactory stereochemical quality of the models as well as common residues in their interface with PcrV. ^[10] The in silico analysis revealed that the rs968697 polymorphism in the promoter region of the HMGA2 gene could influence transcription factor binding, including ATF6, DBP, CDPCR3, DR3, NRSF, PAX8, PPARA, SZF11, TAXCREB and POLR2A. ^[11] RESULTS In silico analysis revealed that of the CASC family only CASC11 showed consistent results considering its differential expression as well as its association with the overall survival of patients. ^[12] In silico analysis revealed the significant postpartum activation of upstream regulators, such as INSR, PPARG, and PPARGC1A. ^[13] In silico analysis revealed increased methylation of both CRFRs in CRC tissue and ccfDNA-derived datasets. ^[14] In silico analysis revealed a possible differential affinity between wild-type and mutant OTCase, while Arg92Gln decreases the binding ability of OTCase to the substrate, which can disrupt the urea cycle and explains the molecular pathogenicity of clinical hyperammonemia. ^[15] In-silico analysis revealed Ser, His, Phe, Tyr and Thr to be present at active site of aminopeptidase B. ^[16] In silico analysis revealed that NOD1 consists of 943 amino acids comprising of one caspase recruitment domain (CARD) at N-terminal, one central NACHT domain and nine leucine rich repeat (LRR) regions at C-terminal. ^[17] In addition, in-silico analysis revealed a strong interaction between FAM107A and β3-AR based on their energy binding score. ^[18] In silico analysis revealed that Thr-Prx are more frequent in all domains of life, while Ser-Prx are more abundant in bacteria. ^[19] In silico analysis revealed that it contains 229 open reading frames and 16 tRNAs. ^[20] Furthermore, the in-silico analysis revealed that this enzyme consists of 233 amino acid residues. ^[21] Further in silico analysis revealed that the newly sequenced hGMB genomes represented 22 previously uncultured species in the Unified Human Gastrointestinal Genome (UHGG) and contributed 24 representatives of potentially “dark taxa” that had not been discovered by UHGG. ^[22] RESULTS In silico analysis revealed that 10 accessions possessed resistant allele of the Pi-ta gene. ^[23] Further in silico analysis revealed the prominent signalling pathways downstream of TGF-β1 in LX-2 cells, which will be useful for improving the understanding of how this cytokine influences broader signalling pathways in the activation of HSCs. ^[24] In-silico analysis revealed the presence of conserved motifs in both AaPCS and anaPCS sequences as well as structural modelling of PCS functional domain was conducted. ^[25] In addition to other OmpAs, in silico analysis revealed that the putative outer membrane protein (OMP) with gene locus PA1041 is a lipoprotein with an OmpA domain and, hence, is a potential virulence factor. ^[26] In silico analysis revealed all of the these significantly down-regulated genes to be putative targets of 9 out of 34 of our predicted viral miRNAs. ^[27] In silico analysis revealed that increased HVEM, but not BTLA, mRNA expression in leukemic cells correlated with diminished overall survival. ^[28] Results High-throughput in silico analysis revealed 9 DEMs hsa-let-7a, hsa-let-7g, hsa-mir-181b, hsa-mir-26b, hsa-mir-30c, hsa-mir-186, hsa-mir-10a, hsa-mir-30b, and hsa-let-7f between ATLL patients and healthy donors. ^[29] In silico analysis revealed that both of them are pathogenic, but later on, Gly116Arg was proven to be more pathogenic by various in silico prediction tools. ^[30] In silico analysis revealed the presence of functional conserved fucose permease (FucP) domain, involved in fructose transport. ^[31] In silico analysis revealed the good binding interaction between amino acid residues of caspase-3 (PDB ID: 1GFW) protein and selected active constituents of MOF. ^[32] In silico analysis revealed that rs25644A/G could act as an intronic cryptic donor site. ^[33] This combined in vivo and in silico analysis revealed that cup placement in relation to the stem is key to the in vivo joint friction and heating-up of THA. ^[34] In silico analysis revealed the prominent signalling pathways downstream of TGF-β1 in LX-2 cells. ^[35] In silico analysis revealed that LWI_ST16 belonged to ST16, an emergent international clone notable for its increased virulence potential. ^[36] In silico analysis revealed the presence of important cis -acting elements related to abiotic stresses and phytohormones. ^[37] In silico analysis revealed that these 11 miRNAs were related to processes involved in the pathogenesis and evolution of ARDS. ^[38] In silico analysis revealed that these genes are well conserved across the vertebrate’s lineage and the mature peptide sequences shared at least 77% of identity with the human homolog. ^[39] Furthermore, in silico analysis revealed that coactivator Med1 potentially associates with 48 (out of 74) obesity-signature genes. ^[40] In silico analysis revealed a comparatively smaller interactome for the Nostoc RecF, RecO and RecR proteins compared to other bacteria, with RecO predicted to interact with both RecF and RecR. ^[41] The in silico analysis revealed that the majority of the compounds have a drug-likeness and good ADMET characteristics. ^[42] In silico analysis revealed that many of the identified SNPs influenced the structure and energy of the hairpin precursors. ^[43] In silico analysis revealed that three crucial ingredients (synephrine, paeoniflorin and naringin) were assumed to coordinate the network of those IBS therapeutic modules by acting on these kernel targets in the important pathways. ^[44] The in silico analysis revealed that compound rhamnetin showed good enzyme inhibition. ^[45] Moreover, in silico analysis revealed that “focal adhesion”, “ECM-receptor”, “endocytosis”, “PI3K-Akt signaling” and “Hippo signaling” were involved in oncogenic pathways in ICC cells. ^[46] Conclusion Together, the in silico analysis revealed the predicted structure of partial S protein, immunogenic properties, and possible regions for S protein of SARS-CoV-2 and provides a valuable prelude for engineering the targeted vaccine or drug against B. ^[47] In silico analysis revealed that the LRM sequence was conserved in cpcA from Bangiales and Florideophyceae, indicating that the novel ACE inhibitory peptide LRM was highly conserved in red algae. ^[48] Further, in silico analysis revealed that high interaction of DAPG encoding protease with lectin which is associated with R. ^[49] Our comprehensive in silico analysis revealed that the expression levels of NAT8, TINAG, and SLC17A1 are highly associated with outcomes of patients with KIRC. ^[50]

silico analysis showed

In silico analysis showed that they grouped into 16 different sequence types and 17 serotypes; the serotypes most frequently identified were O116:H21 and O168:H8 (13% each). ^[1] In silico analysis showed that the variant destabilizes the hydrophobic core and allosterically affects the enzyme activity. ^[2] In silico analysis showed that PGRMC1 inhibition upregulated more genes related to metabolism, molecular transport, and hormonal biosynthesis compared to control dEnSC. ^[3] In silico analysis showed that the peptides identified may display a wide variety of potential biological activities. ^[4] In silico analysis showed that Lys296 of PKR and Lys66 of OAS interact with Hiltonol. ^[5] In silico analysis showed that Foxp3 and coexpressed genes in breast cancer were associated with immune response genes. ^[6] Moreover, in silico analysis showed that the lncRNA MIAT and PTPRG-AS1 may serve as miRNA sponges to regulate D2HGDH, SPNS1, KCND2 and TNFAIP8L3. ^[7] In silico analysis showed that epithelial membrane protein 3 (EMP3) is associated with favorable survival, and negatively regulates cell cycle S-phase. ^[8] SwissTargetPrediction in silico analysis showed that khat constituents cathine, cathinone, catheduline K2, and catheduline E5 bind to family A G-protein-coupled receptor, cause many neurological diseases and disorders such as Alzheimer's, schizophrenia, depression, and anxiety, and induce many ovarian cancer-related diseases. ^[9] The in silico analysis showed that the phyto-constituents of G. ^[10] In silico analysis showed that the 361 G > C SNP has no effect on the physicochemical properties and 3D structure. ^[11] In silico analysis showed a possible shared epitope in the peroxidase protein family. ^[12] The predicted mutant protein had 388 amino acids and in silico analysis showed the variant was considered deleterious. ^[13] In silico analysis showed that their transcriptional region structures, as well as their amino acid sequences, physicochemical characteristics, motifs, conserved domains, and three-dimensional structures of their encoded proteins are highly consistent with their counterparts in the species of Bovidae. ^[14] The in silico analysis showed that the mutation p. ^[15] In silico analysis showed that Transcription Factor AP2-alpha is able to bind to the altered CpG site, suggesting that CpG -3400 may play a functional role in the regulation of ADIPOQ expression. ^[16] In silico analysis showed the effect of variants on FVIII macromolecule stability, which may be the possible mechanism causing the discrepancy. ^[17] In-silico analysis showed that Eleucine calmodulin (EcCaM) has greater similarity to rice CaM as compared to Arabidopsis CaM due to the presence of highly conserved four EF-hand domains. ^[18] The in silico analysis showed that DgeKer is composed of signal peptide, N-terminal propeptide, mature domain, and C-terminal extension. ^[19] In silico analysis showed that Sirt1 and PP2A are prediction targets of miR-141. ^[20] In-silico analysis showed that Eleusine CaM (EcCaM) has greater similarity to rice CaM as compared to Arabidopsis CaM due to the presence of highly conserved four EF-hand domains. ^[21] In silico analysis showed that tritordeum has fewer CD epitopes belonging to the ω-gliadins and a lower LMW-GS than the landrace or modern cv. ^[22] In silico analysis showed that rs7514229, rs3181366, and rs2295800 polymorphisms may affect the transcription of mRNA by regulating miRNA binding, TF binding, and promoter activation, respectively, which may have biological consequences. ^[23] In silico analysis showed high mRNA expression of GPNMB was associated with distant metastasis and GPNMB was overexpressed in TNBC. ^[24] Further characterization and identification using FT-IR, 2D-PAGE, MALDI-TOF, and in-silico analysis showed that the isolated AMP had the highest similarity to Subtilisin-A. ^[25] Results: In silico analysis showed that the model containing (Gly4Ser)3 as a linker has more stability compared with other linkers. ^[26] In silico analysis showed that the variation was predicted to deregulate complement activation by altering the structural properties and enhancing C3b binding capacity to compete with Complement Factor H (CFH), which was in line with experimental data previously published. ^[27] The in silico analysis showed that rs968697 polymorphism located in the promoter region of HMGA2 gene could affect the binding of transcription factors. ^[28] The R545H missense variant has been found at very low allelic frequency in public databases, and in silico analysis showed that this amino acid substitution is predicted to have a damaging role. ^[29] In silico analysis showed that three putative peptidoglycan hydrolases, including N-acetylmuramyl-L-Ala amidase (protein ID: ALT46642. ^[30] In silico analysis showed that the variant is expected to reduce the quality of the splice donor site in intron 10 and causes abnormal splicing. ^[31] In this study, in silico analysis showed that both gene localization and the protein sequences of the three core KEOPS complex members Osgep, Tp53rk and Tprkb are highly conserved across different species including Xenopus laevis. ^[32] In silico analysis showed gradual increase of let-7i-5p and decrease of GALNT1 over time and the combination was validated both in mouse and human miR-gene target prediction databases. ^[33] In silico analysis showed miR-29abc with highest context score and its binding region was conserved among mammals. ^[34] In silico analysis showed that taxifolin can bind to the rapamycin binding site of mTOR and the catalytic site of PI3K (p110α). ^[35] Importantly, in silico analysis showed that the shorter truncation, SHIP2176-298, contained all ordered residues between the SH2 and the PH-R domain, and matched the RhoA effector motif 1 of PKN1 well in sequence alignment, suggesting that SHIP2176-298 is sufficient for further studies on the structure and RhoA binding of SHIP2. ^[36] In-silico analysis showed that it contains bipartite nuclear localization sequence within the conserved NAC domain, post-translational modification sites and belongs to NAM sub-family. ^[37] In silico analysis showed that HOXB5 expression was increased in neuroendocrine PCa (NEPC). ^[38] Our in silico analysis showed that hydrophobic interactions with the active site amino acid residues of the modeled proteins (somatotropin and erythropoietin) were more prevalent than hydrogen bonds and salt bridges that affect the flexibility and stability of the somatotropin and erythropoietin as revealed from our protein flexibility analysis. ^[39] In silico analysis showed that nine significant KEGG pathways and eight significant GO terms were predicted to be enriched upon ZIKVBR infection, and these pathways were related to cancer, environmental information processing, metabolism, and extracellular matrix. ^[40] In silico analysis showed that V. ^[41] In silico analysis showed that various development-associated, phytohormone-responsive, and stress-related cis-acting regulatory elements were enriched in the promoter regions of BnMYB-related genes. ^[42] The results of the performed in silico analysis showed that the high anxiolytic activity of compound 3b is explained by the combination of a pronounced interaction mainly with the benzodiazepine site of the GABAA receptor with a prominent interaction with both the specific and allosteric sites of the 5-HT2A receptor. ^[43] Based on their intensity and occurrence, 13 biomarkers were chosen to compose ribotype-specific profiles, and in silico analysis showed that most of these biomarkers were uncharacterized proteins or well-conserved peptides, such as ribosomal proteins. ^[44] Importantly, in silico analysis showed that the C/T transition at this locus gives rise to two new transcription factor binding sites (TFBS), E2F1 and Nkx3-2. ^[45] In silico analysis showed that g. ^[46] In silico analysis showed that BUB1B was associated with inflamed CD8+, exhausted T-cell signature, IFN-γ signature, and the response to nivolumab. ^[47] However, in silico analysis showed that V460A may possibly be a neutral variant. ^[48] In silico analysis showed that the genomes of these two strains contain genes related to N-acyl-homoserine lactone (AHL) and cellulose biosynthesis, involved in quorum sensing and biofilm formation, which are essential for plant colonization. ^[49] In silico analysis showed that the genome of Delta phage does not encode any known bacterial toxin or virulence factor, determinants of antibiotic resistance and known human allergens. ^[50]

silico analysis predicted

In silico analysis predicted the mutation as “disease causing. ^[1] Moreover, in silico analysis predicted 22 MRE-modulating SNPs and 22 MRE-creating SNPs in the 3'UTR of these candidate genes. ^[2] In silico analysis predicted that Chk2 possesses a Ca2+/calmodulin (CaM) binding motif ahead of its kinase domain. ^[3] In silico analysis predicted that PcOSM has higher binding efficiency with adiponectin receptor compared to adiponectin. ^[4] Initial in silico analysis predicted exons that can be skipped with minimal loss of neurofibromin function. ^[5] In silico analysis predicted that these variants could be pathogenic. ^[6] In silico analysis predicted several abiotic stress-responsive elements in its promoters. ^[7] In silico analysis predicted that many Jagged2 missense variants are associated with structural changes and protein misfolding. ^[8] In silico analysis predicted that the two missense SNPs (rs3218536 and rs1799794) were found to have an impact on the protein structure, stability and function. ^[9] In silico analysis predicted that the β-sheet rich N-terminal collagen-binding domain (CBD) of Cnm has propensity for amyloid aggregation, whereas the threonine-rich C-terminal domain was predicted to be disorganized. ^[10] We finally identified two non-secretor alleles (se610and se357,856,863) and one weak secretor allele (se262,357), while in silico analysis predicted that many alleles impair the function. ^[11] In silico analysis predicted the pathogenicity of this substitution, demonstrated by in vitro assays showing that the p. ^[12] In silico analysis predicted that the β-sheet-rich N-terminal collagen-binding domain (CBD) of Cnm has a propensity for amyloid aggregation, whereas the threonine-rich C-terminal domain was predicted to be disorganized. ^[13] In silico analysis predicted that RMND5A was a potential target of microRNA(miR)-590-5p. ^[14] In silico analysis predicted that p. ^[15] In silico analysis predicted that the 8. ^[16] In silico analysis predicted high OPC affinity with Cyclin D1 (-6. ^[17] Three polymorphic missense variants in homozygous genotype form were found in intron 8 and detected in eight patients, One missense mutation was found in exon 10 in the site of transactivation domain and detected in ten patients and in-silico analysis predicted it as a pathogenic one, Three mutations were found in exon 11 and detected in all patients as a compound homozygous. ^[18] In silico analysis predicted the target gene KDM6A of miR-145. ^[19] Interaction of laccase enzyme with azo dyes using in silico analysis predicted the binding energy with reactive red (−7. ^[20] In conclusion, our in-silico analysis predicted 5 nsSNPs and 22 ncSNPs as potential candidates in the IL-33 gene for future genetic association studies. ^[21] In silico analysis predicted that CaDXR protein contains 21 α-helix and 11 β-sheets and further DXR protein model was validated by Ramachandran plot analysis. ^[22] In vitro proteolysis assays determined that junctophilin-2 is susceptible to proteolysis by MMP-2 and in silico analysis predicted multiple MMP-2 cleavage sites between the membrane occupation and recognition nexus repeats and within the divergent region of junctophilin-2. ^[23] In silico analysis predicted that the mutation was potentially pathogenic. ^[24]

silico analysis suggested

In silico analysis suggested that αKG binds to mouse OXGR1. ^[1] In silico analysis suggested an interaction of miR-494-5p with the 3´UTR of JAK1. ^[2] In silico analysis suggested that the presence of reproductive-associated Tregs in GBM tumors was associated with worse patient outcomes. ^[3] The in silico analysis suggested proteoglycans in cancer as a pathway regulated by the studied miRs and frequently dysregulated miRs in CLL. ^[4] In silico analysis suggested a specific binding site of ORF687 in the coding region, not the 5′ untranslated region estimated previously, of Type A. ^[5] Here, in silico analysis suggested that the special tridomain NDP-heptose synthetases with isomerase, kinase, and nucleotidyltransferase activities are conservatively distributed in Actinobacteria class of Gram-positive bacterium. ^[6] In silico analysis suggested that rs10773771 can change the mRNA secondary structure of PIWIL1 and affect the binding of the miRNAs and regulatory motifs to the 3'-UTR of PIWIL1. ^[7] An in silico analysis suggested presence of the glucanase-like gene in Agrostis, Deyeuxia, and Polypogon genera, but not in other species belonging to the clade 1 of the Poeae tribe. ^[8] In silico analysis suggested that urinary biomarker abnormalities in HF principally reflect changes in collagen turnover and immune response, both associated with fibrosis. ^[9] In silico analysis suggested high homology between human and sturgeon collagen proteins, and ultra-performance liquid chromatography confirmed that both types of cartilage consisted mainly of the same amino acids. ^[10] In silico analysis suggested a possible interaction between the calcium binding domain (CaBD) of OPN and ALK-1 receptor. ^[11] In silico analysis suggested that it may be a deleterious mutation. ^[12] The in-silico analysis suggested that the promoter sequence of MdSMXL8.