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Gorilla gorilla

Gorilla gorilla, also known as the western lowland gorilla, is a critically endangered primate species native to the forests and jungles of Central Africa.
These majestic primates are the largest living primates, known for their impressive size, strength, and distinctive silver-gray backs.
PubCompare.ai offers researchers a powerful tool to explore the latest Gorilla gorilla research, from published literature to pre-prints and patents.
Through seamless comparisons and AI-driven analysis, the platform helps users locate the best protocols and methodologies, enhancing the reproducibility and accuracy of their studies.
Experience the future of research optimization and discover the world of Gorilla gorilla science with PubCompare.ai today.

Most cited protocols related to «Gorilla gorilla»

1
Profiling Human Small RNA Landscape
From the Gene Expression Omnibus (GEO) and Short Reads Archive (SRA) databases, we compiled human small RNA data from 13 studies, comprising altogether 94 distinct data sets from tissues, cell lines and cancers (21–33 ). These data were parsed to fasta format and adapters were clipped (where present) and reads <18 nt were removed with the Mapper module using these options: -h -i -j -k -l -m. Then the data from each set were pooled to generate what we refer to in the following as the ‘undiluted data set’. The 10 diluted data sets were generated by sampling the undiluted data set separately 10 times. For each sampling, each read in the undiluted data set was retained with a probability equal to the dilution fraction (e.g. to generate the 0.1 dilution data set, each read in the undiluted data set was retained with 10% probability and discarded with 90% probability). Each of the ten data sets was processed and mapped against the human hsa v36.3 genome using the Mapper module with these options: –p –s –t. Then each set of data was analyzed by the miRDeep2 module with default options, taking the following input files: reads in fasta format, genome in fasta format, read mappings in .arf format, mature miRNAs from the reference species in fasta format and mature miRNAs from related species in fasta format. miRNAs input were all from miRBase version 16, and P. troglodytes, P. paniscus, G. gorilla and P. pygmaeus were considered related species. For each analysis, the lowest score cut-off that yielded a signal-to-noise ratio of five or higher was used.
Friedländer M.R., Mackowiak S.D., Li N., Chen W, & Rajewsky N. (2011). miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Research, 40(1), 37-52.
Publication 2011
Cell Lines Gene Expression Genome Genome, Human Gorilla gorilla Homo sapiens Malignant Neoplasms MicroRNAs Technique, Dilution Tissues
2
Great Ape Genomic Variation Analysis
We sequenced to a mean coverage of 25X (Illumina HiSeq 2000) a total of 79 great ape individuals, representing 10 subspecies and four genera of great apes from a variety of populations across the African continent and Southeast Asia. SNPs were called using GATK12 (link) after BWA28 (link) mapping to the human genome (NCBI Build 36) using relaxed mapping parameters. Samples combined by species were realigned around putative indels. SNP calling was then performed on the combined individuals for each species. For indels, we used the GATK Unified Genotyper to produce an initial set of indel candidates applying several quality filters and removing variants overlapping segmental duplications and tandem repeats. We also removed groups of indels clustering within 10 bp to eliminate possible artifacts in problematic regions. Conservative allelic imbalance filters were used to eliminate false heterozygotes that may affect demographic analyses, some of which are sensitive to low levels of contamination. We estimate that the application of this filter resulted in a 14% false negative rate for heterozygotes. Our multispecies study design facilitated this assessment of contamination, which may remain undetected in studies focused on assessing diversity within a single species. The amount of cross-species contamination was estimated from the amount of non-endogenous mitochondrial sequence present in an individual. Because we wished to compare patterns of variation between and within species, we report all variants with respect to coordinates of the human genome reference. For FRAPPE analyses, we used MAF0.06 (human, orangutan, and bonobo) and 0.05 (chimpanzee and gorilla) to remove singletons. For most of the analyses, we only used autosomal markers, except in the X/A analysis. To determine the amount of inbreeding, we calculated the heterozygosity genome-wide in windows of 1 Mbp with 200 kbp sliding windows. We then clustered together the neighboring regions to account for runs of homozygosity. For the PSMC analyses, we called the consensus bases using SAMtools29 (link). Underlying raw sequence data is available through the SRA (PRJNA189439/SRP018689). Data generated in this work are available from http://biologiaevolutiva.org/greatape/. A complete description of the material and methods is provided in the Supplementary Note.
Prado-Martinez J., Sudmant P.H., Kidd J.M., Li H., Kelley J.L., Lorente-Galdos B., Veeramah K.R., Woerner A.E., O’Connor T.D., Santpere G., Cagan A., Theunert C., Casals F., Laayouni H., Munch K., Hobolth A., Halager A.E., Malig M., Hernandez-Rodriguez J., Hernando-Herraez I., Prüfer K., Pybus M., Johnstone L., Lachmann M., Alkan C., Twigg D., Petit N., Baker C., Hormozdiari F., Fernandez-Callejo M., Dabad M., Wilson M.L., Stevison L., Camprubí C., Carvalho T., Ruiz-Herrera A., Vives L., Mele M., Abello T., Kondova I., Bontrop R.E., Pusey A., Lankester F., Kiyang J.A., Bergl R.A., Lonsdorf E., Myers S., Ventura M., Gagneux P., Comas D., Siegismund H., Blanc J., Agueda-Calpena L., Gut M., Fulton L., Tishkoff S.A., Mullikin J.C., Wilson R.K., Gut I.G., Gonder M.K., Ryder O.A., Hahn B.H., Navarro A., Akey J.M., Bertranpetit J., Reich D., Mailund T., Schierup M.H., Hvilsom C., Andrés A.M., Wall J.D., Bustamante C.D., Hammer M.F., Eichler E.E, & Marques-Bonet T. (2013). Great ape genetic diversity and population history. Nature, 499(7459), 471-475.
Publication 2013
Allelic Imbalance Genome Genome, Human Gorilla gorilla Heterozygote HIVEP1 protein, human Homo sapiens Homozygote INDEL Mutation Mitochondria Negroid Races Pan paniscus Pan troglodytes Pongidae Pongo pygmaeus Segmental Duplications, Genomic Tandem Repeat Sequences
3
Comprehensive MHC Peptide Binding Dataset
Quantitative nonameric peptide–MHC class I binding data were obtained from the IEDB database (Sette et al. 2005a (link)) and an in-house database of quantitative peptide–MHC binding data. In total, the data set consisted of 79,137 unique peptide–MHC class I interactions covering 34 HLAA, 32 HLA-B, eight chimpanzee (Patr), seven rhesus macaque (Mamu), one gorilla (Gogo), and six mouse MHC class I alleles. See Supplementary Table S1 for a list of the number of data points per allele. The data are highly diverse containing a total number of 25,525 unique peptides. Only a minor fraction of the peptides (1,112 or 4%) share more than seven amino acid identity to any other peptide in the data set. The data set contains a large fraction of non-binding data for each allele (on average 70%). The low data redundancy and the large amount of non-binding data make this an ideal data set for machine learning data mining.
Qualitative nonameric MHC ligand data for HLA-A, HLA-B, HLA-C, and HLA-G were obtained from the SYFPEITHI database (Rammensee et al. 1999 (link)), and MHC ligand data for HLA-E*0101 were obtained from the IEDB (Sette et al. 2005a (link)).
Quantitative data for the swine MHC molecule SLA-1*0401 was obtained as described in the “Materials and methods”.
The evaluation data for HLA ligands and quantitative non-human primate peptide binding are available online at http://www.cbs.dtu.dk/suppl/immunology/NetMHCpan-2.0.php.
Hoof I., Peters B., Sidney J., Pedersen L.E., Sette A., Lund O., Buus S, & Nielsen M. (2008). NetMHCpan, a method for MHC class I binding prediction beyond humans. Immunogenetics, 61(1), 1-13.
Publication 2008
Alleles Amino Acids Genes, MHC Class I Gorilla gorilla Histocompatibility Antigens Class I HLA-B Antigens HLA-C Antigens HLA-E antigen HLA-G Antigen Homo sapiens Ligands Macaca mulatta MHC binding peptide Mice, House Pan troglodytes peptide I Peptides Pigs Primates
4
Hybrid De Novo Genome Assembly
We constructed a hybrid de novo assembly combining 5.4 Gbp of capillary read pairs with the contigs from an initial short read assembly of 166.8 Gbp of Illumina paired reads. Improvements in long-range structure were then guided by human homology, placing contigs into scaffolds wherever read pairs confirmed collinearity between gorilla and human. Base-pair contiguity was improved by local reassembly within each scaffold, merging or extending contigs using Illumina read pairs. Finally we used additional Kamilah BAC and fosmid end pair capillary sequences to provide longer range scaffolding. Base errors were corrected by mapping all Illumina reads back to the assembly and rectifying apparent homozygous variants, while recording the location of heterozygous sites.
Further details and other methods are described in Supplementary Information.
Scally A., Dutheil J.Y., Hillier L.W., Jordan G.E., Goodhead I., Herrero J., Hobolth A., Lappalainen T., Mailund T., Marques-Bonet T., McCarthy S., Montgomery S.H., Schwalie P.C., Tang Y.A., Ward M.C., Xue Y., Yngvadottir B., Alkan C., Andersen L.N., Ayub Q., Ball E.V., Beal K., Bradley B.J., Chen Y., Clee C.M., Fitzgerald S., Graves T.A., Gu Y., Heath P., Heger A., Karakoc E., Kolb-Kokocinski A., Laird G.K., Lunter G., Meader S., Mort M., Mullikin J.C., Munch K., O’Connor T.D., Phillips A.D., Prado-Martinez J., Rogers A.S., Sajjadian S., Schmidt D., Shaw K., Simpson J.T., Stenson P.D., Turner D.J., Vigilant L., Vilella A.J., Whitener W., Zhu B., Cooper D.N., de Jong P., Dermitzakis E.T., Eichler E.E., Flicek P., Goldman N., Mundy N.I., Ning Z., Odom D.T., Ponting C.P., Quail M.A., Ryder O.A., Searle S.M., Warren W.C., Wilson R.K., Schierup M.H., Rogers J., Tyler-Smith C, & Durbin R. (2012). Insights into hominid evolution from the gorilla genome sequence. Nature, 483(7388), 169-175.
Publication 2012
Base Pairing Capillaries Gorilla gorilla Heterozygote Homo sapiens Homozygote Hybrids
5
Detecting Signatures of Selection
To define candidate loci that may have been targeted by selection, we first calculated nSL for all SNPs and then established a cutoff based on the 1st and 99th percentile of the empirical distributions for each population independently. In addition, we assigned P values to each SNP using parametric simulations, as described in the section Estimation of P values. Results are presented by ranking the absolute normalized nSL scores in each population. For the nSL scores in the 1st and 99th percentiles, we performed a hierarchical cluster analysis of the fragment lengths between pairwise differences. Based on this analysis, we determined the number of different haplotypes backgrounds for each allele. This information was used for plotting purposes (visualization of the haplotypes carrying the derived and the ancestral allele).
We used RefSeqGenes (http://www.ncbi.nlm.nih.gov/refseq/rsg/, last accessed March 3, 2014) to assign SNPs to genes, when applicable. For this purpose, we focused solely on genes with transcript products, that is, with mature mRNA. When more than one transcript was available we used the longest transcript product. We then assigned SNPs into genes according to the transcript coordinates. We kept the most extreme score per gene to rank all genes according to this score and performed the Gene Ontology enrichment analysis using the GOrilla tool Eden et al. (2009) with two list of genes; the list of candidates (top 3% of genes) and the list of all genes in the study (from 14,269 to 14,279 genes, depending on the population). Any category belonging to GO process, GO function and GO component was considered significant if having a corrected P value ≤ 0.05. The corrected P value was computed as the P value provided by GOrilla times the number of tested GO terms.
iHS was computed using the code released by Voight et al. (2006) (link). iHS scores were normalized similarly to nSL. The EHH and rEHH were computed with our own code according to the description given by Sabeti (2005) , where the EHH and rEHH of a particular core haplotype t are calculated as follows:

where c is the number of samples of a particular core haplotype, e is the number of samples of a particular extended haplotype, and S is the number of unique extended haplotypes (Sabeti 2005 ).
The rEHH is . And, is the decay of EHH on all other core haplotypes combined:

where n is the number of different core haplotypes (Sabeti 2005 ).
For the purpose of this article, the core haplotypes of interest are defined by the presence or absence of a single SNP.
Ferrer-Admetlla A., Liang M., Korneliussen T, & Nielsen R. (2014). On Detecting Incomplete Soft or Hard Selective Sweeps Using Haplotype Structure. Molecular Biology and Evolution, 31(5), 1275-1291.
Publication 2014
Alleles Genes Gorilla gorilla Haplotypes RNA, Messenger

Most recents protocols related to «Gorilla gorilla»

1
Pancake Coil Design for Inductive Heating
The advantage of a ‘pancake’ coil configuration for IH applications resides in the fact that some of the generated AMF appears on its surface. Therefore, it is suitable for applications that require surface heating and could have some degree of penetration depending on the intensity of the magnetic field. Other geometries, such as a helical configuration, require the target object to be inserted inside the coil [48 (link)–50 (link)]. A ‘pancake’ planar configuration met this project’s goal of applying AMFs to other surfaces. Hence, a 20-turn (for the LIH) and a 30-turn (for the TRIH) miniature multilayer ‘pancake’ coils were wound using a special high-frequency (200–350 kHz) wire known as Litz wire (MSW Wire Industries, Westlake Village, CA, USA). Litz wire is a conductor comprised of many twisted insulated strands that greatly minimizes the skin and proximity effects normally present in conductors at high frequencies by reducing the cross-sectional area of individual conductors [51 (link)]. It also counters the increase of the conductor impedance at higher frequencies, as the wire will maintain an AC resistance similar to its DC resistance. The wire used was composed of 120 strands of 42 AWG tightened with nylon, each one covered by a polyurethane insulation that allows it to withstand temperatures up to 155 °C.
The coils were wound counterclockwise on a nail (⌀ = 1.5 mm) that was inserted on a 10 cm × 10 cm slab of wood. Millimeter grid paper was glued to the wood to ensure the required coil diameter was met. Using this paper as a guide, twenty or thirty turns were made around the nail. Every three turns, Gorilla® Super Glue (Gorilla Glue Company, Cincinnati, OH, USA) was poured on the windings to maintain the turns in place. The coils were then detached from the base with about 5 cm of unwounded wire. Finally, the ends of the coils were soldered to Litz wires of the same gauge on their respective devices. These wires were then soldered to 6 AWG Type 2 Litz wires (OSCO Ltd., Milton Keynes, UK) that run externally and connect directly to the electrical circuitry with set screw copper lugs. The devices were operated at resonance (see Supplementary Information; subsection A). For this particular design, resonance frequencies of 326 kHz and 303 kHz were selected for the LIH and TRIH, respectively. Other values of resonance frequencies (100–500 kHz) can also be obtained using different tuning parameters. Table 1 presents a list of all relevant parameters of the coils used for the LIH and the TRIH cases. See figure 2 for a depiction of the LIH and TRIH coils.
Castro-Torres J.L., Méndez J., Torres-Lugo M, & Juan E. (2023). Development of handheld induction heaters for magnetic fluid hyperthermia applications and in-vitro evaluation on ovarian and prostate cancer cell lines. Biomedical Physics & Engineering Express, 9(3), 035010.
Publication 2023
Copper Electricity Flatulence Gorilla gorilla Helix (Snails) Magnetic Fields Medical Devices Nails Nylons Polyurethanes Skin Vibration Wounds
2
Functional Protein Network Analysis

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Publication 2023
Gene Expression Gorilla gorilla IL31 protein, human Microtubule-Associated Proteins Proteins
3
Sentence Comprehension and Production Study
The experiment was approved by the Research-Innovation Ethics Committee from Universitat Rovira i Virgili, Tarragona, Spain. The whole experiment was conducted in the online platform www.Gorilla.sc. After participants read the experimental instruction and ticked the consent form, they filled out a questionnaire about their language learning background. Participants were automatically directed to the experiment page after passing a short proficiency test. The instructions were displayed on the screen with words, pictures, and audios. They informed participants that they might hear a grammatical or an ungrammatical sentence. While the audio (the stimulus) was played, participants had to press a key as a response when they heard the target word that was displayed on the screen. The target word was presented simultaneously to the entire duration time of the audio stimulus. Participants needed to respond quickly by pressing the key before the experimental webpage automatically switched to the next screen. Participants’ RT for measuring sensitivity was automatically recorded by the online experimental platform when the key was pressed. To further confirm the authenticity of the RT, pictures (including one picture that revealed the situation/content and one unrelated picture) were used to check whether participants understood the meaning of the stimuli sentences. They needed to choose the picture that matched the content of each sentence. Next, participants were guided to repeat the sentences orally using correct English, and their productions were audio recorded. After the instruction, they completed five practical trials and could choose to re-practice if necessary. All their comprehension answers and their utterances were recorded as experimental data. The experimental procedure is shown in Figure 1.
He Q, & Oltra-Massuet I. (2023). An experimental study on grammatical sensitivity and production competence in Chinese and Spanish EFL learners and its implications on EFL teaching methods. Frontiers in Psychology, 14, 1096875.
Publication 2023
Ethics Committees, Research Gorilla gorilla Hearing Hypersensitivity Joints
4
Foamy Virus Env Binding Assay
A flow-cytometry assay was developed by Duda et al. to detect binding of recombinantly expressed Foamy virus Env variants to cells18 (link). By using a panel of SU truncations fused to the Fc region of murine IgG (immunoadhesins) the authors showed that the RBD—defined as the minimal region of the PFV Env sufficient for binding to cells—encompassed residues 225 to 555 (corresponding to residues 226 to 552 in gorilla FV RBD (GII-K74 strain, accession number JQ867464)44 (link) (Fig. S6)). When designing the expression construct for SFV RBD, we also considered the secondary prediction generated by the Phyre2 webserver45 (link). Residue I225 was in the middle of a putative helix (residues 220–230), leading us to choose an upstream residue R218 as the N-terminus of the construct (Fig. 1a and Fig. S6).
The information on secondary structure predictions, obtained by Phyre2 webserver was also used to design the Env ectodomain construct, which starts after the first predicted transmembrane helix (S91) and encompasses residues up to I905.
Fernández I., Dynesen L.T., Coquin Y., Pederzoli R., Brun D., Haouz A., Gessain A., Rey F.A., Buseyne F, & Backovic M. (2023). The crystal structure of a simian Foamy Virus receptor binding domain provides clues about entry into host cells. Nature Communications, 14, 1262.
Publication 2023
Biological Assay Cells Flow Cytometry Gorilla gorilla Helix (Snails) Mus Strains
5
Online Behavioral and fMRI Study
Experiments complied with all relevant ethical regulations, and were approved by the Ethics Committee of the University of Amsterdam, The Netherlands (2017-EXT-8201, 2018-EXT-8864, 2020-EXT-12450). Two independent experiments were performed: an Online behavioral study and an fMRI study. Behavior was tested in a larger sample of participants, but this had to be done online, using the Online platform Gorilla (https://gorilla.sc/), due to COVID-19 restrictions in place at the time. Brain activity was measured in a smaller number of participants in our fMRI scanner. Table 1 gives an overview of the number of participants and experimental conditions included in each study.
Fornari L., Ioumpa K., Nostro A.D., Evans N.J., De Angelis L., Speer S.P., Paracampo R., Gallo S., Spezio M., Keysers C, & Gazzola V. (2023). Neuro-computational mechanisms and individual biases in action-outcome learning under moral conflict. Nature Communications, 14, 1218.
Publication 2023
Brain COVID 19 Ethics Committees fMRI Gorilla gorilla

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More about "Gorilla gorilla"

Explore the world of western lowland gorillas (Gorilla gorilla), the largest living primates, known for their impressive size, strength, and distinctive silver-gray backs.
These critically endangered species are native to the forests and jungles of Central Africa.
Researchers can utilize powerful tools like PubCompare.ai to delve into the latest Gorilla gorilla research, from published literature and pre-prints to patents.
The platform's seamless comparisons and AI-driven analysis help users locate the best protocols and methodologies, enhancing the reproducibility and accuracy of their studies.
Discover how Gorilla gorilla research can be optimized through the use of cutting-edge techniques and technologies.
Leverage the power of TRIzol reagent, HiSeq 2000 and HiSeq 2500 sequencing platforms, RNeasy Mini Kit, RNAlater, and RNeasy kit for RNA extraction and purification.
Analyze your samples with the Agilent 2100 Bioanalyzer, a robust tool for assessing RNA quality and quantity.
Explore the applications of GORILLA Glass, a durable and scratch-resistant material, in various research and technological domains.
Experience the future of research optimization and uncover the latest advancements in Gorilla gorilla science with PubCompare.ai today.