Pairwise and higher-order epistatic effects among somatic cancer mutations across oncogenesis

Cancer occurs as a consequence of multiple somatic mutations that lead to uncontrolled cell growth. Mutual exclusivity and co-occurrence of mutations imply-but do not prove-that mutations exert synergistic or antagonistic epistatic effects on oncogenesis. Knowledge of these interactions, and the consequent trajectories of mutation and selection that lead to cancer has been a longstanding goal within the cancer research community. Recent research has revealed mutation rates and scaled selection coefficients for specific recurrent variants across many cancer types. However, there are no current methods to quantify the strength of selection incorporating pairwise and higher-order epistatic effects on selection within the trajectory of likely cancer genotoypes. Therefore, we have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation (flux), dependent on somatic cancer genotype. Coupling this continuous-time Markov chain model with a deconvolution approach provides estimates of underlying mutation rates and selection across the trajectory of oncogenesis. We demonstrate computation of fluxes and selection coefficients in a somatic evolutionary model for the four most frequently variant driver genes (TP53, LRP1B, KRAS and STK11) from 565 cases of lung adenocarcinoma. Our analysis reveals multiple antagonistic epistatic effects that reduce the possible routes of oncogenesis, and inform cancer research regarding viable trajectories of somatic evolution whose progression could be forestalled by precision medicine. Synergistic epistatic effects are also identified, most notably in the somatic genotype TP53 LRP1B for mutations in the KRAS gene, and in somatic genotypes containing KRAS or TP53 mutations for mutations in the STK11 gene. Large positive fluxes of KRAS variants were driven by large selection coefficients, whereas the flux toward LRP1B mutations was substantially aided by a large mutation rate for this gene. The approach enables inference of the most likely routes of site-specific variant evolution and estimation of the strength of selection operating on each step along the route, a key component of what we need to know to develop and implement personalized cancer therapies.

Identification of neoplasm-specific signatures of miRNA interactions by employing a systems biology approach

MicroRNAs represent major regulatory components of the disease epigenome and they constitute powerful biomarkers for the accurate diagnosis and prognosis of various diseases, including cancers. The advent of high-throughput technologies facilitated the generation of a vast amount of miRNA-cancer association data. Computational approaches have been utilized widely to effectively analyze and interpret these data towards the identification of miRNA signatures for diverse types of cancers. Herein, a novel computational workflow was applied to discover core sets of miRNA interactions for the major groups of neoplastic diseases by employing network-based methods. To this end, miRNA-cancer association data from four comprehensive publicly available resources were utilized for constructing miRNA-centered networks for each major group of neoplasms. The corresponding miRNA-miRNA interactions were inferred based on shared functionally related target genes. The topological attributes of the generated networks were investigated in order to detect clusters of highly interconnected miRNAs that form core modules in each network. Those modules that exhibited the highest degree of mutual exclusivity were selected from each graph. In this way, neoplasm-specific miRNA modules were identified that could represent potential signatures for the corresponding diseases.

Use of Mutual Exclusivity and its Relationship to Language Ability in Toddlers with Autism Spectrum Disorder

To efficiently learn new words, children use constraints such as mutual exclusivity (ME) to narrow the search for potential referents. The current study investigated the use of ME in toddlers with autism spectrum disorder (ASD) and neurotypical (NT) peers matched on nonverbal cognition. Thirty-two toddlers with ASD and 26 NT toddlers participated in a looking-while-listening task. Images of novel and familiar objects were presented along with a novel or familiar label. Overall, toddlers with ASD showed less efficient looking toward a novel referent when a novel label was presented compared to NT toddlers, controlling for age and familiar word knowledge. However, toddlers with ASD and higher language ability demonstrated more robust use of ME than those with lower language ability.

Cross-Situational Word Learning With Multimodal Neural Networks

In order to learn the mappings from words to referents, children must integrate co-occurrence information across individually ambiguous pairs of scenes and utterances, a challenge known as cross-situational word learning. In machine learning, recent multimodal neural networks have been shown to learn meaningful visual-linguistic mappings from cross-situational data, as needed to solve problems such as image captioning and visual question answering. These networks are potentially appealing as cognitive models because they can learn from raw visual and linguistic stimuli, something previous cognitive models have not addressed. In this paper, we examine whether recent machine learning approaches can help explain various behavioral phenomena from the psychological literature on cross-situational word learning. We consider two variants of a multimodal neural network architecture and look at seven different phenomena associated with cross-situational word learning and word learning more generally. Our results show that these networks can learn word-referent mappings from a single epoch of training, mimicking the amount of training commonly found in cross-situational word learning experiments. Additionally, these networks capture some, but not all of the phenomena we studied, with all of the failures related to reasoning via mutual exclusivity. These results provide insight into the kinds of phenomena that arise naturally from relatively generic neural network learning algorithms, and which word learning phenomena require additional inductive biases.

Mutual Exclusivity in Pragmatic Agents

One of the great challenges in word learning is that words are typically uttered in a context with many potential referents. Children's tendency to associate novel words with novel referents, which is taken to reflect a mutual exclusivity (ME) bias, forms a useful disambiguation mechanism. We study semantic learning in pragmatic agents-combining the Rational Speech Act model with gradient-based learning-and explore the conditions under which such agents show an ME bias. This approach provides a framework for investigating a pragmatic account of the ME bias in humans but also for building artificial agents that display an ME bias. A series of analyses demonstrates striking parallels between our model and human word learning regarding several aspects relevant to the ME bias phenomenon: online inference, long-term learning, and developmental effects. By testing different implementations, we find that two components, pragmatic online inference and incremental collection of evidence for one-to-one correspondences between words and referents, play an important role in modeling the developmental trajectory of the ME bias. Finally, we outline an extension of our model to a deep neural network architecture that can process more naturalistic visual and linguistic input. Until now, in contrast to children, deep neural networks have needed indirect access to (supposed to be novel) test inputs during training to display an ME bias. Our model is the first one to do so without using this manipulation.

Fast mutual exclusivity algorithm nominates potential synthetic lethal gene pairs through brute force matrix product computations

Mutual Exclusivity analysis of genomic aberrations contributes to the exploration of potential synthetic lethal (SL) relationships thus guiding the nomination of specific cancer cells vulnerabilities. When multiple classes of genomic aberrations and large cohorts of patients are interrogated, exhaustive genome-wide analyses are not computationally feasible with commonly used approaches. Here we present Fast Mutual Exclusivity (FaME), an algorithm based on matrix multiplication that employs a logarithm-based implementation of the Fisher's exact test to achieve fast computation of genome-wide mutual exclusivity tests; we show that brute force testing for mutual exclusivity of hundreds of millions of aberrations combinations can be performed in few minutes. We applied FaME to allele-specific data from whole exome experiments of 27 TCGA studies cohorts, detecting both mutual exclusivity of point mutations, as well as allele-specific copy number signals that span sets of contiguous cytobands. We next focused on a case study involving the loss of tumor suppressors and druggable genes while exploiting an integrated analysis of both public cell lines loss of function screens data and patients' transcriptomic profiles. FaME algorithm implementation as well as allele-specific analysis output are publicly available at https://github.com/demichelislab/FaME.

Twelve-month-olds disambiguate new words using mutual-exclusivity inferences

Representing objects in terms of their kinds enables inferences based on the long-term knowledge made available through kind concepts. For example, children readily use lexical knowledge linked to familiar kind concepts to disambiguate new words (e.g., "find the toma"): they exclude members of familiar kinds falling under familiar kind labels (e.g., a ball) as potential referents and link new labels to available unfamiliar objects (e.g., a funnel), a phenomenon dubbed as 'mutual exclusivity'. Younger infants' failure in mutual exclusivity tasks has been commonly interpreted as a limitation of early word-learning or inferential abilities. Here, we investigated an alternative explanation, according to which infants do not spontaneously represent familiar objects under kind concepts, hence lacking access to the information necessary for rejecting them as referents of novel labels. Building on findings about conceptual development and communication, we hypothesized that nonverbal communication could prompt infants to set up kind-based representations which, in turn, would promote mutual exclusivity inferences. This hypothesis was tested in a looking-while-listening task involving novel word disambiguation. Twelve-month-olds saw pairs of objects, one familiar and one unfamiliar, and heard familiar kind labels or novel words. Across two experiments providing a cross-lab replication in two different languages, infants successfully disambiguated novel words when the familiar object had been pointed at before labeling, but not when it had been highlighted in a non-communicative manner (Experiment 1) or not highlighted at all (Experiment 2). Nonverbal communication induced infants to recruit kind-based representations of familiar objects that they failed to recruit in its absence and that, once activated, supported mutual-exclusivity inferences. Developmental changes in children's appreciation of communicative contexts may modulate the expression of early inferential and word learning competences.

Prediction error boosts retention of novel words in adults but not in children

How do we update our linguistic knowledge? In seven experiments, we asked whether error-driven learning can explain under what circumstances adults and children are more likely to store and retain a new word meaning. Participants were exposed to novel object labels in the context of more or less constraining sentences or visual contexts. Both two-to-four-year-olds (M_age = 38 months) and adults were strongly affected by expectations based on sentence constraint when choosing the referent of a new label. In addition, adults formed stronger memory traces for novel words that violated a stronger prior expectation. However, preschoolers' memory was unaffected by the strength of their prior expectations. We conclude that the encoding of new word-object associations in memory is affected by prediction error in adults, but not in preschoolers.

A greedy approach for mutual exclusivity analysis in cancer study

The main challenge in cancer genomics is to distinguish the driver genes from passenger or neutral genes. Cancer genomes exhibit extensive mutational heterogeneity that no two genomes contain exactly the same somatic mutations. Such mutual exclusivity (ME) of mutations has been observed in cancer data and is associated with functional pathways. Analysis of ME patterns may provide useful clues to driver genes or pathways and may suggest novel understandings of cancer progression. In this article, we consider a probabilistic, generative model of ME, and propose a powerful and greedy algorithm to select the mutual exclusivity gene sets. The greedy method includes a pre-selection procedure and a stepwise forward algorithm which can significantly reduce computation time. Power calculations suggest that the new method is efficient and powerful for one ME set or multiple ME sets with overlapping genes. We illustrate this approach by analysis of the whole-exome sequencing data of cancer types from TCGA.

Linking disambiguation and retention in a developmental eye-tracking study with monolingual and multilingual children

The disambiguation effect, also referred to as process of elimination, occurs during word learning, whereby novel words are mapped onto new referents, precluding the application of a novel label to a familiar object. Prior studies showed that the emergence and use of disambiguation can be affected by children's vocabulary growth and linguistic experience, such as growing up with more than one language. To test this, we investigated (a) whether monolingual and multilingual children disambiguated a novel word-object mapping, (b) whether they retained a trained, previously seen word-object mapping, (c) whether they retained the novel fast-mapped word-object mapping, and (d) whether and how age, English vocabulary size, and language background modulated disambiguation and retention. Lastly, we tested (e) whether children who disambiguated also retained better. Eye-tracking data from 18- to 30-month-old monolingual children (n = 43) and multilingual children (n = 40) were collected. A looking-while-listening paradigm with two objects included two familiar items, one novel item, and one trained item. Mixed-effect models reported that vocabulary size predicted the outcome of mapping and retention better than age. Monolingual children's accuracy on disambiguation trials was high from the start, whereas multilingual children started to disambiguate later as their vocabulary grew. Only monolingual children performed above chance level on retaining the novel label. Lastly, the use of disambiguation improved retention for monolingual children but not for multilingual children. This research corroborates that disambiguation should be regarded as a mechanism facilitating default fast mapping rather than fully fledged learning. Vocabulary growth leading to an increase in disambiguation supports the notion that the disambiguation effect stems from prior episodes of learning.

Identification of common signatures in idiopathic pulmonary fibrosis and lung cancer using gene expression modeling

Background

Idiopathic pulmonary fibrosis (IPF) is associated with an increased risk for lung cancer, but the underlying mechanisms driving malignant transformation remain largely unknown. This study aimed to identify differentially expressed genes (DEGs) distinguishing IPF and lung cancer from healthy individuals and common genes driving the transformation from healthy to IPF and lung cancer.

Methods

The gene expression data for IPF and non-small cell lung cancer (NSCLC) were retrieved from the Gene Expression Omnibus (GEO) database. The DEG signatures were identified via unsupervised two-way clustering (TWC) analysis, supervised support vector machine analysis, dimensional reduction, and mutual exclusivity analysis. Gene enrichment and pathway analyses were performed to identify common signaling pathways. The most significant signature genes in common among IPF and lung cancer were further verified by immunohistochemistry.

Results

The gene expression data from GSE24206 and GSE18842 were merged into a super array dataset comprising 86 patients with lung disorders (17 IPF and 46 NSCLC) and 51 healthy controls and measuring 23,494 unique genes. Seventy-nine signature DEGs were found among IPF and NSCLC. The peroxisome proliferator-activated receptor (PPAR) signaling pathway was the most enriched pathway associated with lung disorders, and matrix metalloproteinase-1 (MMP-1) in this pathway was mutually exclusive with several genes in IPF and NSCLC. Subsequent immunohistochemical analysis verified enhanced MMP1 expression in NSCLC associated with IPF.

Conclusions

For the first time, we defined common signature genes for IPF and NSCLC. The mutually exclusive sets of genes were potential drivers for IPF and NSCLC.

The role of speaker eye gaze and mutual exclusivity in novel word learning by monolingual and bilingual children

The current study examined the combined effect of a speaker's eye gaze and mutual exclusivity (ME) on novel word retention in monolingual and bilingual children. A novel object was presented with a familiar object, and children were taught new labels for objects under two conditions. In the Align condition, the speaker's gaze and the ME cue provided the same information (the speaker looked at the novel object while labeling it with a novel name). In the Conflict condition, the speaker's gaze and the ME cue provided competing information (the speaker looked at the familiar object while labeling it with a novel name). Using a visual world eye-tracking paradigm, children's retention was assessed by testing novel objects with novel labels and by testing the familiar objects with novel labels. We found that all children successfully retained the novel labels for novel objects when both eye gaze and ME provided the same information. However, when the cues conflicted, bilingual children did not perform above chance for either novel objects or familiar objects. In contrast, monolingual children demonstrated retention of novel labels for familiar objects but not for novel objects. Together, the findings suggest that redundant cues benefit word retention in all children regardless of linguistic background. Furthermore, when speaker gaze and ME conflict, bilingual children appear to disregard both cues during retention, whereas monolingual children may be more willing to retain novel labels for familiar words, suggesting that they prioritize a speaker's eye gaze over ME.

The role of developmental change and linguistic experience in the mutual exclusivity effect

Given a novel word and a familiar and a novel referent, children have a bias to assume the novel word refers to the novel referent. This bias - often referred to as "Mutual Exclusivity" (ME) - is thought to be a potentially powerful route through which children might learn new word meanings, and, consequently, has been the focus of a large amount of empirical study and theorizing. Here, we focus on two aspects of the bias that have received relatively little attention in the literature: Development and experience. A successful theory of ME will need to provide an account for why the strength of the effect changes with the age of the child. We provide a quantitative description of the change in the strength of the bias across development, and investigate the role that linguistic experience plays in this developmental change. We first summarize the current body of empirical findings via a meta-analysis, and then present two experiments that examine the relationship between a child's amount of linguistic experience and the strength of the ME bias. We conclude that the strength of the bias varies dramatically across development and that linguistic experience is likely one causal factor contributing to this change. In the General Discussion, we describe how existing theories of ME can account for our findings, and highlight the value of computational modeling for future theorizing.

When knowing only one word for "car" leads to weak application of mutual exclusivity

From a very young age, monolingual children assume their language has no synonyms, or use the principle of mutual exclusivity (only one label per object). In contrast, bilingual children often accept more novel synonyms than monolinguals. One possible explanation for this difference is the lexicon structure hypothesis: having synonyms (across languages) in the lexicon reduces adherence to mutual exclusivity. The purpose of this study is to test the lexicon structure hypothesis by comparing three- to five-year-old children who speak either Canadian French or English. Canadian French allows more synonyms than English. French-speaking children should therefore accept more novel synonyms than English-speaking children. The children did a disambiguation task, choosing whether a familiar or an unfamiliar object was the referent of a novel word (e.g., moli). Surprisingly, the French-speaking children accepted significantly fewer novel synonyms than English-speaking children. However, they accepted the most synonyms for objects that had synonyms in French but they did not know both synonyms. These results support a modified version of the lexicon structure hypothesis, one that accounts for children's weak access to synonyms.

Linguistic conventionality and the role of epistemic reasoning in children's mutual exclusivity inferences

To interpret an interlocutor's use of a novel word (e.g., "give me the papaya"), children typically exclude referents that they already have labels for (like an "apple"), and expect the word to refer to something they do not have a label for (like the papaya). The goal of the present studies was to test whether such mutual exclusivity inferences require children to reason about the words their interlocutors know and could have chosen to say: e.g., If she had wanted the "apple" she would have asked for it (since she knows the word "apple"), so she must want the papaya. Across four studies, we document that both children and adults will make mutual exclusivity inferences even when they believe that their interlocutor does not share their knowledge of relevant, alternative words, suggesting that such inferences do not require reasoning about an interlocutor's epistemic states. Instead, our findings suggest that children's own knowledge of an object's label, together with their belief that this is the conventional label for the object in their language, and that this convention applies to their interlocutor, is sufficient to support their mutual exclusivity inferences. Additionally, and contrary to the claims of previous studies that have used mutual exclusivity as a proxy for children's beliefs that others share their knowledge, we found that children - especially those with stronger theory of mind ability - are quite conservative about attributing their knowledge of object labels to others. Together, our findings hold implications for theories of word learning, and for how children learn about the scope of shared conventional knowledge.

Detection of Combinatorial Mutational Patterns in Human Cancer Genomes by Exclusivity Analysis

Cancer genes may tend to mutate in a co-mutational or mutually exclusive manner in a tumor sample of a specific cancer, which constitute two known combinatorial mutational patterns for a given gene set. Previous studies have established that genes functioning in different signaling pathways can mutate in the same sample, i.e., a tumor from one patient, while genes operating in the same pathway are rarely mutated in the same cancer genome. Therefore, reliable identification of combinatorial mutational patterns of candidate cancer genes has important ramifications in inferring signaling network modules in a particular cancer type. While algorithms for discovering mutated driver pathways based on mutual exclusivity of mutations in cancer genes have been proposed, a systematic pipeline for identifying both co-mutational and mutually exclusive patterns with rational significance estimation is still lacking. Here, we describe a reliable framework with detailed procedures to simultaneously explore both combinatorial mutational patterns from public cross-sectional gene mutation data.

Learning how to use a tool: Mutually exclusive tool-function mappings are selectively acquired from linguistic in-group models

The current study investigated whether 4-year-olds used language as a cue to social group membership to infer whether the tool-use behavior of a model needed to be encoded as indicative of the tool's function. We built on children's tendency to treat functions as mutually exclusive, that is, their propensity to refrain from using the same tool for more than one function. We hypothesized that children would form mutually exclusive tool-function mappings only if the source of the function information was a linguistic in-group person (native) as opposed to an out-group (foreign) person. In Experiment 1, participants (N = 39) were presented with four tool-function pairs by a model who had previously spoken either in their native language or in a foreign language. During the test phase, children encountered new purposes for which they could either use the demonstrated tools' color variant or use another equally suitable, as yet unseen, alternative tool. In line with our predictions, children preferred to use the alternative tool for the new function only in the native language condition (native: 63.3%; foreign: 42.7%). Experiment 2 replicated the initial finding using another foreign language and demonstrated that the lack of mutually exclusive tool choice in the foreign condition did not originate from children's failure to encode the demonstration. These findings suggest that children restrict learning artifact functions from linguistic in-group models. The mutual exclusivity principle in the domain of function learning is used more flexibly than previously proposed.

CM-viewer: Visualizing interaction network of co-mutated and mutually exclusively mutated cancer genes

Cancer genes usually play a crucial role in regulating cell growth. Normal cells transform into malignant tumors by the acquisition of accumulated genetic mutations that enable them to evade normal growth control. It is therefore important to understand the relationships between mutations during cancer development and progression. Although cancer genes with co-occurring and mutually exclusive mutations have already been studied on different scales, there is no timely updated interaction network available for co-mutated and mutually exclusively mutated cancer genes. Therefore, we firstly downloaded 567 cancer genes from COSMIC (catalogue of somatic mutations in cancer) cancer gene census. Secondly, somatic mutations of 71 cancer genomics projects were downloaded from the ICGC (International Cancer Genome Consortium) data portal. Thirdly, mutated cancer genes and affected donors were extracted from the ICGC data to form a mutation matrix where rows are genes, columns are donors, 1 denotes occurrence, and 0 denotes absence of mutation. Afterwards, co-mutated and mutually exclusively mutated cancer gene pairs were identified using DISCOVER (discrete independence statistic controlling for observations with varying event rates). Finally, CM-viewer was developed to visualize the interaction network of cancer genes with co-occurring and mutually exclusive mutations. It is an online visualization tool as well as a biological database. It promises to understand how gene mutations contribute to tumorigenesis and to identify key biomarkers and drug targets for cancer. CM-viewer is freely available at http://www.zhounan.org/comutgene.

Does sound structure affect word learning? An eye-tracking study of Danish learning toddlers

Previous research has shown that Danish-learning children lag behind in early lexical acquisition compared with children learning a number of other languages. This delay has been ascribed to the opaque phonetic structure of Danish, which appears to have fewer reliable segmentation cues than other closely related languages. In support of this hypothesis, recent work has shown that the phonetic properties of Danish negatively affect online language processing in young Danish children. In this study, we used eye-tracking to investigate whether the challenges associated with processing Danish also affect how Danish-learning children between 24 and 35 months of age establish and learn novel label-object mappings. The children were presented with a series of novel mappings, either ostensively (one novel object presented alone on the screen) or ambiguously (one novel object presented together with a familiar one), through carrier phrases with different phonetic structures (more vs less opaque). Our results showed two main trends. First, Danish-learning children performed poorly on the task of mapping novel labels onto novel objects. Second, when learning did occur, accuracy was affected by the phonetic opacity of the speech stimuli. We suggest that this finding results from the interplay of a perceptually challenging speech input and a slower onset of early vocabulary experience, which in turn may delay the onset of word learning skills in Danish-learning children.

Isocitrate dehydrogenases in physiology and cancer: biochemical and molecular insight

Isocitrate dehydrogenases play important roles in cellular metabolism and cancer. This review will discuss how the roles of isoforms 1 and 2 in normal cell and cancer metabolism are distinct from those of isoform 3. It will also explain why, unlike 1 and 2, mutations in isoform 3 in tumor are not likely to be driver ones. A model explaining two important features of isocitrate dehydrogenases 1 and 2 mutations, their dominant negative effect and their mutual exclusivity, will be provided. The importance of targeting these mutations and the possibility of augmenting such therapy by targeting other cancer-related pathways will also be discussed.

A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence

In cancer, mutually exclusive or co-occurring somatic alterations across genes can suggest functional interactions. Existing tests for such patterns make the unrealistic assumption of identical gene alteration probabilities across tumors. We present Discrete Independence Statistic Controlling for Observations with Varying Event Rates (DISCOVER), a novel test that is more sensitive than other methods and controls its false positive rate. A pan-cancer analysis using DISCOVER finds no evidence for widespread co-occurrence, and most co-occurrences previously detected do not exceed expectation by chance. Many mutual exclusivities are identified involving well-known genes related to cell cycle and growth factor signaling, as well as lesser known regulators of Hedgehog signaling.

An exact algorithm for finding cancer driver somatic genome alterations: the weighted mutually exclusive maximum set cover problem

Background

The mutual exclusivity of somatic genome alterations (SGAs), such as somatic mutations and copy number alterations, is an important observation of tumors and is widely used to search for cancer signaling pathways or SGAs related to tumor development. However, one problem with current methods that use mutual exclusivity is that they are not signal-based; another problem is that they use heuristic algorithms to handle the NP-hard problems, which cannot guarantee to find the optimal solutions of their models.

Method

In this study, we propose a novel signal-based method that utilizes the intrinsic relationship between SGAs on signaling pathways and expression changes of downstream genes regulated by pathways to identify cancer signaling pathways using the mutually exclusive property. We also present a relatively efficient exact algorithm that can guarantee to obtain the optimal solution of the new computational model.

Results

We have applied our new model and exact algorithm to the breast cancer data. The results reveal that our new approach increases the capability of finding better solutions in the application of cancer research. Our new exact algorithm has a time complexity of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O^{*}(1.325^{m})$$\end{document}O∗(1.325m)(Note: Following the recent convention, we use a star * to represent that the polynomial part of the time complexity is neglected), which has solved the NP-hard problem of our model efficiently.

Conclusion

Our new method and algorithm can discover the true causes behind the phenotypes, such as what SGA events lead to abnormality of the cell cycle or make the cell metastasis lose control in tumors; thus, it identifies the target candidates for precision (or target) therapeutics.

Electronic supplementary material

The online version of this article (doi:10.1186/s13015-016-0073-9) contains supplementary material, which is available to authorized users.

The influence of bilingualism on statistical word learning

Statistical learning is a fundamental component of language acquisition, yet to date, relatively few studies have examined whether these abilities differ in bilinguals. In the present study, we examine this issue by comparing English monolinguals with Chinese-English and English-Spanish bilinguals in a cross-situational statistical learning (CSSL) task. In Experiment 1, we assessed the ability of both monolinguals and bilinguals on a basic CSSL task that contained only one-to-one mappings. In Experiment 2, learners were asked to form both one-to-one and two-to-one mappings, and were tested at three points during familiarization. Overall, monolinguals and bilinguals did not differ in their learning of one-to-one mappings. However, bilinguals more quickly acquired two-to-one mappings, while also exhibiting greater proficiency than monolinguals. We conclude that the fundamental SL mechanism may not be affected by language experience, in accord with previous studies. However, when the input contains greater variability, bilinguals may be more prone to detecting the presence of multiple structures.

Lexicon structure and the disambiguation of novel words: evidence from bilingual infants

In ambiguous word learning situations, infants can use systematic strategies to determine the referent of a novel word. One such heuristic is disambiguation. By age 16-18months, monolinguals infer that a novel noun refers to a novel object rather than a familiar one (Halberda, 2003), while at the same age bilinguals and trilinguals do not reliably show disambiguation (Byers-Heinlein & Werker, 2009; Houston-Price, Caloghiris, & Raviglione, 2010). It has been hypothesized that these results reflect a unique aspect of the bilingual lexicon: bilinguals often know many translation equivalents, cross-language synonyms such as English dog and Mandarin gǒu. We studied the role of vocabulary knowledge in the development of disambiguation by relating 17-18month-old English-Chinese bilingual infants' performance on a disambiguation task to the percentage of translation equivalents in their comprehension vocabularies. Those bilingual infants who understood translation equivalents for more than half the words in their vocabularies did not show disambiguation, while infants who knew a smaller proportion of translation equivalents showed disambiguation just as same-aged monolinguals do. These results demonstrate that the structure of the developing lexicon plays a key role in infants' use of disambiguation.